This study examines the antecedents of the intention to maintain engagement in consumer-to-consumer transactions for virtual goods on the Steam Community Market (SCM), a prominent online gaming platform. Applying the 3M model, the research links core personality traits to loyalty to the Steam market, considering the mediating roles of user attitude, gaming network size, and perceived value. Survey data from 157 Brazilian SCM users submitted to structural equation modeling accounted for roughly 84% of the variance in the intention to keep transacting virtual goods in the Steam market. The results show how important it is to look at both compound personality traits and value perception when trying to connect abstract personality traits to loyalty in virtual item markets.

PurposeThis study frames sustainable consumption as a dimension of social responsibility and investigates how economic constraints, infrastructural asymmetries, consumer values (environmental and egoistic) and the informal market influence both individual choices and access to sustainable food systems. Focusing on a developing-country context, the study aims to examine the contextual determinants shaping the intention-behavior relationship in sustainable food consumption. In doing so, it addresses a research gap by extending insights beyond the predominance of studies conducted in developed economies.Design/methodology/approachData were collected from 645 consumers of organic food in southern Brazil using a mixed sampling strategy comprising in-person surveys at an organic fair and an online questionnaire distributed via social media. To test the conceptual model, data were analyzed using partial least squares structural equation modeling with SPSS and SmartPLS software.FindingsEnvironmental values positively affect attitudes, whereas egoistic values negatively influence them. Attitude, subjective norms and perceived behavioral control significantly predict intention. Locavorism strengthens, whereas price sensitivity and convenience orientation weaken the intention-behavior relationship. These results indicate that sustainable food behavior in developing economies is shaped not only by personal attitudes but also by structural conditions limiting equitable participation in sustainable consumption.Practical implicationsStrengthening local food networks through institutional support and policy interventions can enhance equitable access to sustainable options. Reducing certification costs, improving short supply chains and investing in logistical infrastructure are essential measures to remove systemic barriers and promote inclusive sustainable consumption.Social implicationsThis study positions sustainable food practices as a social responsibility issue, showing how consumer behavior intersects with broader equity concerns. Addressing affordability and convenience constraints is essential to ensure that sustainable options are accessible to all socio-economic groups, rather than remaining exclusive privileges.Originality/valueBy examining the intention-behavior gap in a developing-market context and situating it within systemic constraints such as affordability, infrastructure and informal retail channels, this research contributes to a more inclusive and socially responsible understanding of sustainable consumption. The findings provide context-specific insights that extend existing models of consumer behavior and inform policy and managerial strategies in emerging economies. Future research could extend the egoistic value construct by incorporating food-specific self-oriented motives, such as health consciousness or status-driven consumption.

“Just Accepted” papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence. This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To assess the impact of scanner manufacturer and scan protocol on the performance of deep learning models to classify prostate cancer (PCa) aggressiveness on biparametric MRI (bpMRI). Materials and Methods In this retrospective study, 5,478 cases from ProstateNet, a PCa bpMRI dataset with examinations from 13 centers, were used to develop five deep learning (DL) models to predict PCa aggressiveness with minimal lesion information and test how using data from different subgroups—scanner manufacturers and endorectal coil (ERC) use (Siemens, Philips, GE with and without ERC and the full dataset)—impacts model performance. Performance was assessed using the area under the receiver operating characteristic curve (AUC). The impact of clinical features (age, prostate-specific antigen level, Prostate Imaging Reporting and Data System [PI-RADS] score) on model performance was also evaluated. Results DL models were trained on 4,328 bpMRI cases, and the best model achieved AUC = 0.73 when trained and tested using data from all manufacturers. Hold-out test set performance was higher when models trained with data from a manufacturer were tested on the same manufacturer (within-and between-manufacturer AUC differences of 0.05 on average, P < .001). The addition of clinical features did not improve performance ( P = .24). Learning curve analyses showed that performance remained stable as training data increased. Analysis of DL features showed that scanner manufacturer and scan protocol heavily influenced feature distributions. Conclusion In automated classification of PCa aggressiveness using bpMRI data, scanner manufacturer and endorectal coil use had a major impact on DL model performance and features. Published under a CC BY 4.0 license.

PurposeThis study explores the factors influencing customers' willingness to disclose personal information (WDPI) in electronic banking (e-banking), with a focus on how fear of artificial intelligence (AI) moderates these relationships. Grounded in privacy calculus theory, the research model incorporates personalization, financial literacy, satisfaction and loyalty as key predictors of WDPI.Design/methodology/approachA survey was administered to 408 e-banking users in Portugal, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM).FindingsResults show that personalization and loyalty have a positive impact on WDPI, while financial literacy negatively affects it. Satisfaction indirectly influences WDPI through loyalty. Fear of AI moderates two key pathways: it diminishes the positive effect of personalization and amplifies the negative impact of financial literacy on WDPI. The model accounts for 36% of the variance in WDPI.Originality/valueThis study advances the understanding of information disclosure in digital banking by integrating cognitive (e.g. financial literacy and personalization) and emotional (e.g. fear of AI) dimensions. It highlights how psychological responses to AI shape customer behavior, offering novel insights for e-banking service personalization strategies and privacy management.

PurposeArtificial intelligence tools such as virtual agents (VAs) and chatbots allow retailers to tailor services and strengthen customer interaction. This study investigates the primary factors shaping customer intentions to use and collaborate with virtual agents, with particular attention to the moderating effect of service task type - support, purchase or complaint.Design/methodology/approachThis study empirically tests a model in which perceived ease of use, perceived usefulness and attitude toward virtual agents (antecedents) influence intention to use and willingness to collaborate (outcomes), with service task type assessed as a moderating variable. The model is evaluated using PLS-SEM based on survey data from 691 service customers.FindingsThe results indicate that (1) perceived usefulness, compared to ease of use, is a stronger antecedent of attitude; (2) attitude significantly influences intention to use and willingness to collaborate with virtual agents; (3) attitude functions as a significant mediator between perceived usefulness and intention to use. In addition, the study establishes that service task type - support, purchase or complaint - acts as a significant moderating factor.Practical implicationsThis study shows that customers' intentions to use and interact with virtual agents are mainly shaped by their attitudes and perceived usefulness, with the type of service task performed acting as a relevant contextual factor.Originality/valueThis study makes a distinct contribution by identifying the significant moderating role of customer service tasks in transforming customer attitudes into intentions to adopt virtual agents, offering valuable insights into the mechanisms driving VA adoption in retail and service settings.

Background: Pancreatic ductal adenocarcinoma (PDAC) is a common and lethal cancer. From diagnosis to disease staging, response to neoadjuvant therapy assessment and patient surveillance after resection, imaging plays a central role, guiding the multidisciplinary team in decision-planning. Review aims and findings: This review discusses the most up-to-date imaging recommendations, typical and atypical findings, and issues related to each step of patient management. Example cases for each relevant condition are presented, and a structured report for disease staging is suggested. Conclusion: Despite current issues in PDAC imaging at different stages of patient management, the radiologist is essential in the multidisciplinary team, as the conveyor of relevant imaging findings crucial for patient care.

This study investigates the intersection of digital transformation, business resilience, and marketing capabilities, focusing on small businesses and startups. The digital revolution has significantly transformed business operations, supply chain management, and overall organizational performance. Conducted following PRISMA guidelines, this systematic literature review used the Scopus database, refining an initial 247 documents to 51 relevant studies. Key trends include the vital role of digital transformation in enhancing resilience, the use of emerging technologies for sustainable supply chains, and the importance of digital skills and knowledge management. Research highlights the implications of digital marketing and e-commerce adoption for SMEs, revealing the need for firms to develop dynamic capabilities to thrive in turbulent environments. However, gaps remain, such as understanding the long-term impacts of digital transformation, the interactions between digital maturity, innovation, and sustainability, and the necessity for comparative studies across industries and regions. Additionally, investigating how marketing capabilities contribute to resilience is essential, enabling small businesses and startups to withstand and recover from disruptions. Addressing these trends and gaps will enhance our understanding of digital transformation’s multifaceted implications for SMEs and startups, helping them leverage marketing capabilities to navigate challenges and seize opportunities in the digital era.

Objective: besides free access to online games that adopt the free-to-play business model, players may purchase items to customize the game’s appearance in a consumer-to-consumer (C2C) marketplace. However, the aesthetic value of the virtual items has yet to receive attention in the literature. For this type of game, this study examines a conceptual model of user participation in purchasing virtual goods, testing the relationships between perceived value dimensions (aesthetic, functional, and economic), continued usage intention, and word-of-mouth (WOM) recommendation, with attitude as a mediating factor. Methods: a survey sample of 157 Brazilian users was analyzed with structural equation modeling. Results: the three types of perceived value were supported as antecedents of attitude, which mediates the relationships between perceived value and the consequent intentions of reuse and WOM recommendation. The model’s overall fit index is 64.61%, and its explanatory power is 44% for continued use intention and 64% for WOM recommendation. Conclusions: this study advances the understanding of the dynamics of C2C markets for virtual goods through an empirical analysis of the antecedents of loyalty, including the aesthetic dimension of perceived value. The findings indicate where the platforms can improve, for example, reinforcing the aesthetic value of virtual goods to promote connections with and among users, thus increasing continued use and WOM recommendation.

Despite being one of the most prevalent forms of cancer, prostate cancer (PCa) shows a significantly high survival rate, provided there is timely detection and treatment. Computational methods can help make this detection process considerably faster and more robust. However, some modern machine-learning approaches require accurate segmentation of the prostate gland and the index lesion. Since performing manual segmentations is a very time-consuming task, and highly prone to inter-observer variability, there is a need to develop robust semi-automatic segmentation models. In this work, we leverage the large and highly diverse ProstateNet dataset, which includes 638 whole gland and 461 lesion segmentation masks, from 3 different scanner manufacturers provided by 14 institutions, in addition to other 3 independent public datasets, to train accurate and robust segmentation models for the whole prostate gland, zones and lesions. We show that models trained on large amounts of diverse data are better at generalizing to data from other institutions and obtained with other manufacturers, outperforming models trained on single-institution single-manufacturer datasets in all segmentation tasks. Furthermore, we show that lesion segmentation models trained on ProstateNet can be reliably used as lesion detection models.

Building more sustainable markets requires a combination of resources and motivations to overcome the structural barriers that exist at the different social levels. Farmers are powerful agents who can overcome these barriers to promote more sustainable food systems. By adopting the theoretical perspective of markets as aggregate systems, this study aims to present the barriers faced by farmers and the motivations that stimulate them to act toward forming a more sustainable market system. Our empirical research comprises in-depth interviews with 21 organic food farmers in the southern region of Brazil. The results suggest a complex relationship between structure and agency at the different social levels, which can lead to particular motivations for a sustainable food production system. Finally, we theorize about producers’ roles and how they act to realign different social levels to build more sustainable food markets.

To determine the role of diffusion-weighted imaging (DWI) for predicting response to neoadjuvant therapy (NAT) in pancreatic cancer. MEDLINE, EMBASE, and Cochrane Library databases were searched for studies evaluating the performance of apparent diffusion coefficient (ADC) to assess response to NAT. Data extracted included ADC pre- and post-NAT, for predicting response as defined by imaging, histopathology, or clinical reference standards. ADC values were compared with standardized mean differences. Risk of bias was assessed using the Quality Assessment of Diagnostic Studies (QUADAS-2). Of 337 studies, 7 were included in the analysis (161 patients). ADC values reported for the pre- and post-NAT assessments overlapped between responders and non-responders. One study reported inability of ADC increase after NAT for distinguishing responders and non-responders. A correlation with histopathological response was reported for pre- and post-NAT ADC in 4 studies. DWI’s diagnostic performance was reported to be high in three studies, with a 91.6–100 •The role of DWI with ADC measurements for assessing response to neoadjuvant therapy in pancreatic cancer is still unclear. •Pre- and post-neoadjuvant therapy ADC values overlap between responders and non-responders. •DWI has a reported high diagnostic performance for determining response when using histopathological or clinical reference standards; however, studies are still few and at high risk for bias.

Urinary incontinence is one of the main concerns for patients after radical prostatectomy. Differences in surgical experience among surgeons could partly explain the wide range of frequencies observed. Our aim was to evaluate the association between the surgeons` experience and center caseload with relation to urinary continence recovery after Retzius-sparing robot-assisted radical prostatectomy (RS-RARP). Prospective observational single-center study. Five surgeons consecutively operated 405 patients between July 2017 and February 2022. Continence recovery was evaluated with pad count and by employing the short form of the International Consultation on Incontinence Questionnaire (ICIQ-SF), pre- and postoperatively at 1 year. Non-parametric tests were used. Median age was 63 years, 30% of patients presented with local advanced disease; the positive surgical margin rate (over 3 mm length) was 16%. Complication rate was 1% (Clavien–Dindo > II). One year after surgery, continence was assessed in 282 patients, of whom 87% were pad free and 51% never leaked (ICIQ-SF = 0). With respect to the mean annual number of procedures per surgeon, divided in < 20, 20–39 and ≥ 40, pad-free rates were achieved in 93%, 85%, and 84% and absence of urine leak rates in 47%, 62% and 48% of patients, respectively. Postoperative median ICIQ-SF was five. We acknowledge the limitation of a 12-month follow-up and the fact that we are a medium-volume center. There is no statistically significant association between continence recovery, surgeon’s experience and center caseload. Continence recovery at 1 year after surgery is adequate and robust to surgeon’s experience.

There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability is still a challenge. With this goal in mind, several model training approaches were compared: removing unstable features according to the intraclass correlation coefficient (ICC); training independently with features extracted from each radiologist's mask; training with the feature average between both radiologists; extracting radiomic features from the intersection or union of masks; and creating a heterogeneous dataset by randomly selecting one of the radiologists' masks for each patient. The classifier trained with this last resampled dataset presented with the lowest generalization error, suggesting that training with heterogeneous data leads to the development of the most robust classifiers. On the contrary, removing features with low ICC resulted in the highest generalization error. The selected radiomics dataset, with the randomly chosen radiologists, was concatenated with deep features extracted from neural networks trained to segment the whole prostate. This new hybrid dataset was then used to train a classifier. The results revealed that, even though the hybrid classifier was less overfitted than the one trained with deep features, it still was unable to outperform the radiomics model.

Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) has emerged as a surgical option for patients with prostatic cancer in high-volume centers. The objective is to assess oncological and functional outcomes when implementing RS-RARP in a medium-volume center without previous experience of robotic surgery. This is a prospective observational single-center study. Patients operated between July 2017 and April 2020 were divided into two consecutive groups, A and B, each with 104 patients. The surgeons had prior experience in laparoscopic surgery and underwent robotic training. Positive surgical margin (PSM) status, urinary continence, and erectile function projected by Kaplan–Meier curves, together with patient reported quality of life outcomes at 12 months post-surgery were documented. Median patient age was 63 years (IQR = 59–67), overall PSM rate were 33%, 28% for pT2 disease. Pre-operative values showed no significant difference between both groups. The rate of urinary continence dropped from 81 to 78% (SE = 5.7) (Group A) and from 90 to 72% (SE = 6.3) (Group B) using the International Consultation on Incontinence Questionnaire-Short Form. Baseline sexual function was regained in 41% (Group A) and 47% (Group B) of patients. The median Expanded Prostate Index Composite-26 total score decreased from 86 to 82. These outcomes relate favorably to prior reports. There was a clinically significant decrease in median operative time in the successive groups with post-operative complications occurring in less than 2% of surgical procedures overall. A 12-month follow-up suggests that RS-RARP may be safely introduced in a medium-volume center without previous experience of robotic surgery.

Many m-gov adoption models have been proposed, which can confound researchers and policymakers. In this article, we reviewed 17 studies on m-gov adoption, identifying 25 different factors. We conducted two focus groups to discuss the adequacy of these factors, generating the first version of a unified model. We tested this model using data from 806 survey respondents from Brazil. The proposed unified model is parsimonious and outperforms other theoretical models.

Purpose This study investigates impulse buying as a consumer behaviour outcome in omnichannel retail through the stimulus-organism-response ( S - O - R ) theory. For such, the authors addressed convenience and channel integration as the stimuli, the relationship among consumer empowerment, trust, satisfaction, and perceived value as the organism, and impulse buying as the response. Design/methodology/approach An online survey was conducted with 229 customers of a Brazilian retailer that adopts the omnichannel strategy. Data were analysed by partial least squares structural equation modelling (PLS-SEM). Findings Channel integration and convenience had a positive influence on consumer empowerment which, in turn, influenced customer satisfaction and trust, producing direct and indirect effects on their perception of value relative to the retailer. In addition, impulsive buying was significantly influenced by perceived value. Practical implications The results indicate that retailers that use the omnichannel strategy need to be alert to the factors mentioned above. The study empirically demonstrates that investing in channel integration increases customer empowerment, which will significantly improve customer trust and satisfaction and, eventually, customer impulse buying from the retailer. Originality/value This work contributes to the literature on marketing and consumer behaviour by identifying factors that influence consumers' impulse buying behaviour in the context of omnichannel retail. It suggests that impulse buying may be a relevant variable to understand the reaction of consumers empowered by the integration of the marketing channels and the convenience offered to them in an omnichannel retail environment.

This study investigates coopetition among the 16 semiconductor firms that figured among the top 10 by revenue from 2009 to 2019 using patent data obtained from the Derwent World Patents Index™ (DWPI), considering records available for the selected firms published and indexed up to July 26, 2020. Only 1791 (0.17%) records from a total of more than 1.1 million have two or more of these competing firms as assignees (i.e., they are records for joint patents involving these firms), indicating the existence of coopetition in this scenario. These joint patents demonstrate coopetition between firms from different countries and in the main areas in which their patents are classified, indicating that they may coopete in those areas. Furthermore, mergers and acquisitions and joint ventures may influence coopetition and innovation, resulting in joint patents. Finally, a framework that consolidates the main findings is presented to guide future research. We contribute to the coopetition literature with novel inputs. From a managerial perspective, the findings can be used to build strategies to better exploit the potential of patents.

Information technology (IT) has impacted firms in different industries. IT adoption is just as impactful for small and medium enterprises (SMEs). Despite the number of studies investigating outcomes and IT adoption, there is a lack of consensus regarding the most relevant factors associated with IT adoption by SMEs (e.g. drivers and IT adoption). The study investigates the main antecedents, outcomes, and moderators of IT adoption by SMEs. A meta-analysis was conducted, integrating the findings from 59 studies. Data were analyzed by integrating meta-analysis and regression approach (MASEM). The results showed that the dimensions of TAM (usefulness and ease of use) and perceived compatibility have the strongest correlations among the nine antecedents. The findings indicated that resources and market turbulence were the main predictors of IT adoption in SMEs when testing only the direct relationships (MASEM). IT adoption significantly impacted outcomes, and SMEs from countries with low uncertainty avoidance presented stronger effects of IT adoption on firm outcomes. This research contributes to the literature by (i) addressing prior studies’ conflicts about antecedents and outcomes of SMEs IT adoption, (ii) integrating different theoretical approaches, and (iii) generating insights for managers and public policy institutions responsible for the survival and development of SMEs.

RESUMO Este estudo verificou os determinantes que influenciam o comportamento de consumidores de moda sustentável, incorporando à Teoria do Comportamento Planejado os fatores: obrigação moral, consciência das consequências e o comportamento anterior de compra sustentável. Para isso, realizou-se uma survey com consumidores brasileiros de moda sustentável, e um total de 179 respostas foi analisado por meio da Modelagem de Equações Estruturais de Mínimos Quadrados Parciais (PLS-SEM). Os resultados indicaram que a obrigação moral e a consciência das consequências impactaram a atitude comportamental dos consumidores de moda sustentável. Outrossim, dos três componentes da TPB, apenas a atitude e o controle comportamental percebido influenciaram a intenção de compra. Finalmente, verificou-se que o consumo real de moda sustentável é explicado pela intenção e pelo comportamento de compra anterior, sendo que a variável idade moderou a relação entre intenção e o consumo de moda. Este estudo fornece aos profissionais de marketing informações abrangentes sobre os determinantes psicológicos, sociais, culturais e demográficos do comportamento de compra desses produtos.