Purpose This study aims to examine the relationship between digital transformation search volume and stock returns in the Vietnamese stock market. Design/methodology/approach The authors collected weekly data from Google Trends and vn.investing.com, spanning from week 33 of 2019 to week 32 of 2023. Using this data set, the authors used various quantitative approaches, including VAR-Granger, Ordinary Least Squares (OLS) and Copula, to test the relationships between variables. Findings The results obtained from VAR-Granger analysis reveal a unidirectional causality from digital transformation search volume to the stock returns of VN-Index, VN-30 and VN-100. Findings from the OLS indicate a negative lagged impact of search volume on digital transformation for stock returns. Moreover, using the Copula approach, the authors determine that the structural dependency between the search volume for digital transformation and the VN-Index follows a normal distribution. This suggests that simultaneous positive and negative changes between the variables are equally likely to occur. Research limitations/implications The study is meaningful further research. Practical implications The study is meaningful for stakeholders: investors and policymakers. Originality/value By offering these insights, this paper contributes to a deeper understanding of the relationship between digital transformation and firm performance within the stock exchange market.

Purpose The purpose of this study is to apply the Elaboration Likelihood Model (ELM) to examine persuasive information processing in live streaming commerce (LSC). This study examines the impact of streamer credibility, viewer mindfulness and control variables (age, gender, viewing frequency and subscription status) on purchase and response intentions in the Indonesian context. Design/methodology/approach This study uses Partial Least Squares Structural Equation Modeling to analyze responses from 372 individuals aged 18–45 years who had watched or purchased through LSC within the past month. The model incorporates streamer expertise and sociodemographic control variables. Findings The peripheral route, driven by streamer credibility (trustworthiness, attractiveness and expertise) and co-viewer engagement, strongly influences the persuasiveness of information more than the central route. Viewers are more influenced by social cues than by the quality of product information. Mindfulness does not significantly moderate the relationship between perceived persuasiveness and either purchase or response intention. However, younger, active subscribers demonstrate a higher likelihood of engagement. Research limitations/implications These findings contribute to practical enhancements in streamer branding and digital trust-building strategies, enabling LSC platforms to optimize content and strengthen collaborations with streamers and key opinion leaders, thereby increasing purchase and response intentions. Practical implications The findings of this study offer actionable recommendations for brands and streamers, including strategies to enhance streamer appeal and create persuasive content that resonates with target audiences. Social implications This study fosters stronger, trust-based interactions between streamers and their audiences, promoting inclusive digital economic growth across diverse demographic segments in Indonesia. Originality/value By integrating ELM with streamer credibility, mindfulness and sociodemographic factors, this study provides novel insights into viewer behavior in Indonesia’s emerging LSC landscape.

Purpose The purpose of this paper is to identify and assess the influence of behavioral change agents for adopting green innovation to enhance sustainability performance. Design/methodology/approach This paper employed a quantitative approach by disseminating a structured questionnaire to 141 supply chain professionals of manufacturing firms who are familiar with green innovation, operating in the metropolitan city of Pakistan, i.e. Karachi. Later, exploratory and confirmatory factor analyses were performed to evaluate the reliability and validity of the model. Lastly, SmartPLS was used to test the proposed hypotheses in the study. Findings The findings revealed that green transformational leadership, acceptance of change and work culture showed a significant impact on green innovation leading toward sustainable performance. Research limitations/implications The authors suggest that green innovation is a prime factor for enhancing a firm’s sustainability in the market and supply chain, requiring continuous improvement efforts from supply chain professionals. Practical implications The findings can help decision-makers to increase the efficiency and production of the organization and provide support to green policy-makers. It also empowers employees and fosters green awareness, ultimately generating benefits that serve the company’s best interests. Social implications The study supports a shift toward sustainable behavior, encouraging organizations to contribute positively to society and the environment. Empowering change agents can catalyze pro-environmental attitudes and behaviors, ultimately encouraging organizations to adopt eco-friendly innovations for broader societal and environmental well-being. Originality/value This paper is an initial effort to assess organizational behavioral change on green innovation for enhancing the sustainable performance of manufacturing firms in Pakistan.

Purpose This study aims to examine the trajectories through which individuals evolve into prosumers, focusing on the transition from personal practices to collective influence through social media. Design/methodology/approach This study used a multimethod qualitative approach, combining netnography and in-depth interviews, to analyze prosumer profiles on Instagram and YouTube. This allowed for real-time observation of prosumption activities, interactions and the development of practices within digital communities. Findings The findings reveal a transformation trajectory comprising three interconnected spheres of prosumption: individual prosumption, collective prosumption and professional prosumption. Each sphere is associated with specific triggers, skill development, challenges and accomplishments. Based on these dimensions, the authors introduce the Prosumer Trajectory Framework. Research limitations/implications This study contributes to the prosumption literature by mapping distinct developmental pathways and highlighting the diverse motivations and processes that shape prosumption within digital environments. Practical implications The insights offer practical value to companies and managers seeking to engage with prosumers. By understanding the different stages of their trajectories, organizations can design targeted actions and foster strategic partnerships. Social implications This study highlights the growing cultural influence of prosumers, demonstrating how social media facilitates community building and enhances consumer agency in shaping collective influence. Originality/value By delineating the spheres of the prosumer trajectory, this research advances the conceptualization of prosumption as a transformative process. It offers a unique perspective on how individual, offline practices evolve into digital, public and potentially professional forms of engagement within the contemporary marketplace.

Purpose The paper aims to identify suitable conditional variance models for the estimation and forecasting of cryptocurrency returns volatility. Design/methodology/approach The methodology comprises the use of GARCH-family models estimated by maximum likelihood considering different scedastic functions, number of parameters and error distributions. A cross-validation approach is conducted under different market dynamics to provide robust results. Findings Results indicated that the best GARCH methods for digital coins volatility modeling and forecasting are those associated with a small number of parameters, allowing for asymmetric volatility behavior and considering normal/student distributions. Research limitations/implications The findings indicated that volatility behaves differently for each evaluated cryptocurrency, and the selection of the best scedastic function depends on the corresponding digital coin more than the period under evaluation. Practical implications Investors should prefer parsimonious GARCH structures when modeling and forecasting cryptocurrency volatility, and must consider the current state of the market as the methods lose accuracy in high-volatile periods. Social implications The work provides a better understanding of the volatility dynamics of cryptocurrencies, providing evidence of more accurate tools for risk management in this volatile market. Further, better-informed investors on the risks associated with this market are less susceptible to high price variations. Originality/value The research presents an extensive experimental study to identify the optimal GARCH structure for modeling and forecasting return volatility in digital currencies, considering various market conditions and digital coins, which yields more robust results.

Purpose This article aims to investigate the relationship between business model adaptation, company performance and digitalization capability among startups during the coronavirus disease-2019 pandemic to determine whether there is a correlation among these aspects in uncertainty scenarios. Design/methodology/approach The research used a mixed approach. First, it utilized a survey-based data collection method in which over 400 Brazilian startups participated, representing diverse demographic and cultural characteristics. Following the data analysis, the authors interviewed startup founders who participated in the first phase to enrich the discussion section. Findings The results revealed that startups with stronger digital capabilities and higher performance were associated with lower levels of business model adaptation. However, this association was observed primarily in the dimensions of value creation and value capture, and not in value delivery. Research limitations/implications The limitation of this study includes the cross-sectional data collection, which prevents the assessment of causality between variables. Practical implications The findings suggest that startups should carefully evaluate their business models and adaptation strategies during uncertain periods. Social implications The social implications of this study lie in supporting public policies and initiatives for entrepreneurship and startups. Government agencies and support institutions can use the findings to better understand the challenges faced by startups during uncertain times, effectively guiding their assistance and resources. Originality/value This research contributes to the literature on business models and digitalization capability. It offers insights into the interplay between performance, digital capabilities and business model adaptation. Furthermore, the study contradicts the common sense that businesses should favor adaptation in uncertain moments, at least for startups in similar contexts.

Purpose The paper aims to develop a pioneering assessment index for private policies targeting food loss and waste (FLW) reduction. Design/methodology/approach Starting with a review of seminal works on FLW, identifies variables related to corporate actions addressing FLW, process efficiency and sustainability. This process ensures that the developed indicators are robust, adaptable and suitable for diverse food processing organizations. The model’s applicability is enhanced by its alignment with publicly disclosed corporate reports, allowing a practical interface between theoretical development and market realities. Findings Introduces eight strategic indicators for evaluating private policies, FLW reduction policies, process innovations, measurement methodologies, partnerships, environmental actions, communication and the use of natural resources (water and energy). These indicators enable a nuanced evaluation of how organizations operationalize FLW strategies in markets with varying levels of development. Research limitations/implications The indicators’ effectiveness may vary depending on sectoral and regional specificities. Although this study focuses on food processing organizations, the model’s adaptability to different industries and geographical contexts offers potential avenues for further exploration. Practical implications The model provides organizations with a robust tool to monitor and refine FLW reduction strategies using transparent, evidence-based metrics. The indicators can evaluate organizational actions comparatively, across different entities or overtime, facilitating continuous improvement. Social implications Implementing FLW prevention strategies at the organizational level improves efficiency, reduces costs and promotes equitable resource allocation and environmental preservation. By applying these indicators, companies can enhance their contributions to societal goals. Originality/value An unprecedented assessment model tailored to private FLW policies, filling a critical gap in the literature. Its originality lies in its ability to operationalize sustainability in corporate contexts, enabling stakeholders to evaluate actions consistently across markets with diverse developmental profiles. The indicators’ versatility underscores their potential as a transformative tool for researchers, practitioners and policymakers.