User Innovation Research Articles

Study on Fintech Adoption: Examining the Customer Innovativeness and Attitude Towards the Adoption of Fintech Services

Technology plays an important role in the area of finance and now it become common among people. but whatever the technological advancement in the field of finance, many people are there who don’t have access to formal financial institutions and many researchers found that this can be solved with the help of technology adoption. Here the study focused on the Fintech adoption among the people with the help of the variables Fintech adoption, perceived ease of use, perceived usefulness, user innovation and the attitude towards the financial technology. the researcher utilized both primary and secondary data. Then the samples were selected from Pattambi taluk of Palakkad district-Kerala, based on convenience sampling method and distributed the questionnaire among 300 respondents. then 250 samples were selected from 300 by considering the data accuracy. Then the researcher utilized descriptive statistics and t-test, correlation coefficient, and regression analysis to conclude then the factor analysis was also utilized to understand the relation between the observed variable and the latent constructs. The study discovered that perceived usefulness and perceived ease of use have a stronger correlation with Fintech adoption. then there is a positive correlation between the customer's perceived usefulness of Fintech adoption and their attitude towards it. To increase customer satisfaction, Fintech companies can develop their services based on the perceived usefulness, ease of use, and attitude of customers in particular segments

Artificial intelligence, financial services knowledge, government support, and user innovativeness: Exploring the moderated-mediated path to fintech adoption

Based upon an extended Technology Acceptance Model (TAM), this study aims to investigate the impact of financial services knowledge, familiarity with the use of artificial intelligence, government support, and user innovativeness on Fintech adoption from the perspective of university students. Furthermore, the study also aims to investigate the mediating role of user innovativeness in this relationship. A cross-sectional, survey-based method was used to collect data from 410 university students. Structural equation modeling was implied to examine the research framework of the study. The findings confirm that financial services knowledge, familiarity with artificial intelligence, government support, and user innovativeness have a direct positive impact on Fintech adoption among university students. The results also show that perceived ease of use slightly moderates the relationship between government support and user innovativeness. Meanwhile, results from the mediation analysis reveal an indirect effect of these variables on Fintech adoption through user innovativeness. The study's findings recommend practical suggestions to academic institutes and Fintech service providers to equip university students with the necessary financial knowledge and familiarity with artificial intelligence across various disciplines, which can be achieved through sufficient government support. All these can potentially revolutionize Fintech services adoption and boost economic growth, specifically in Asia-Pacific developing countries. The study identifies the key antecedents that affect the student's decision to adopt Fintech. It widens the scope of Fintech adoption by considering the university students who may serve as the future managers for the nation. It provides nuanced evidence on the role of financial services knowledge and familiarity with the use of artificial intelligence on the intention to adopt Fintech among university students in Asia-Pacific developing countries like Pakistan.

Conditional Potential User Mining framework via explainable surrogate models

User prediction aims to identify the user who show potential value in e-commerce platforms. Existing user prediction algorithms primarily focus on distinguishing between potential user, those likely to purchase a specific product in the future, and non-potential user, those unlikely to do so. However, these algorithms often overlook a valuable group named conditional potential user in non-potential group. Conditional potential user, initially categorized as non-potential, can convert into potential user under specific converted condition (e.g., product trial, coupon receipt, or certification attainment). Additionally, conventional user prediction models do not offer insights into the associated converted condition and provide classification results only. Furthermore, the lack of explainability in user prediction methods limits their practical utility. To tackle these challenges, this paper proposes a definitive concept for conditional potential users and introduces an innovative user prediction framework, the Conditional Potential User Mining (CPUM). Addressing the challenge of predicting conditional potential users, CPUM employs a Gold Standard Classifier to ascertain users’ intentions, thereby identifying their interest in target products under converted conditions and enabling the prediction of conditional potential users. Moreover, CPUM adopts an explainable surrogate model with an attention mechanism to boost explainability. This model is designed to mirror the decision-making capacity of the Gold Standard Classifier and provides importance explanations for different user interactions. This enables precise identification of converted conditions in conditional potential users, thus enhancing explainability. The effectiveness of this method is substantiated by experimental results derived from extensive e-commerce datasets from Alibaba and Amazon, demonstrating its cutting-edge performance and applicability.

The Impact of Artificial Intelligence on Reducing the Learning Curve in 3D Modelling: Enhancing User Experience through Automation and Personalized Assistance.

The purpose of this research paper is to analyse the effects of Artificial Intelligence in 3D modelling software applications to the user experience with an understanding of how the incorporation of automated processes can alleviate the steep learning curve felt by first time users. Concisely the study focuses on the degree to which assistance offered and the tools that helps to manage the work flow improve the accessibility for inexperienced users. Thus, the paper employing the analysis of the degrees of user satisfaction and productivity targeted by these automatic features will illustrate the contribution of these features to the improvement of the modelling environment, targeting the higher percentage of users’ engagement and successful 3D design project implementation. Therefore the study affirms the hypothesis that AI aids in easing the complexities in software hence creating breakthrough creativity and innovation for first time users.

The Effect of Social Presence on User's Participation Willingness Under Tourism Live Streaming

ABSTRACTTourism live streaming, as a powerful online platform connecting destinations and users, has promoted the recovery of tourism in the post‐epidemic era. This study uses the stimulus‐organism‐response (SOR) framework to investigate the connections among social presence, perceived value, and user's participation willingness in tourism activities. Through analyzing 383 responses collected from Douyin users, it is confirmed that social presence and emotional social presence will positively affect users' participation willingness. In addition, perceived functional value and perceived affective value play a partial positive mediating role, and user innovativeness positively moderates the connection between perceived value and users' participation willingness. This study is helpful for anchors and platforms to achieve better tourism live broadcast operation and management and is helpful for the tourism service industry to expand product influence and business performance.

Mechanical and microstructural properties of municipal solid waste incinerator bottom ash (MSWIBA) concrete exposed to salt erosion and drying-wetting cycles

In cold and saline soil areas, concretes usually experience multi-factor erosions, such as freezing-thawing cycles (FTCs), drying-wetting cycles (D-Ws), and salt erosion. To promote green and sustainable development of the construction industry, municipal solid waste incinerator bottom ash (MSWIBA) was adopted as a partial replacement for conventional fine aggregates in concretes. In this study, the coupled effects of the D-Ws and salt erosion (i.e., 5 % NaCl solution and 5 % Na2SO4 solution) were experimentally conducted to investigate the mechanical and microstructural properties of ordinary and MSWIBA concretes. The results showed that D-Ws had a negative effect on the mechanical properties of concretes. The depth and width of cracks in concretes increased with the D-Ws raised. During the D-Ws, the influence of salt solution on concretes could be divided into two stages. Initially, the filling effect of salt crystals was beneficial to the development of concrete strength. Subsequently, salt crystals accumulated in concretes caused cracks, and accelerated the deterioration of concrete specimens. Meanwhile, sodium sulphate reacted with hydration products in concretes to produce some expansive substances, the evident diffraction peaks of expansive substances (e.g., gypsum and ettringite) had been clearly observed after D-Ws. Thus, the damage effect of 5 % Na2SO4 solution (SS) to concrete structure was more serious than that of water (WT) and 5 % NaCl solution (CS). Furthermore, the total porosity of the concrete specimens generally decreased with the MSWIBA substitution rate increased. There was an optimal MSWIBA content for concretes to obtain the excellent mechanical and microstructural properties. In detail, when the substitution rate of MSWIBA was between 0 % and 33.0 %, it had an excellent effect on improving the pore structure of concretes. Specifically, the compressive strength of concretes was larger than 35.0 MPa when the substitution rate of MSWIBA with natural river sand was between 24.8 % and 57.8 %, whereas the substitution rate of MSWIBA should not exceed 33.0 % exposed to D-Ws. This study could provide a significant reference for the sustainable development of concretes in cold and saline soil areas, as well optimization and innovation usage of MSWIBA.

Digital Forensics for Analyzing Cyber Threats in the XR Technology Ecosystem within Digital Twins

Recently, advancements in digital twin and extended reality (XR) technologies, along with industrial control systems (ICSs), have driven the transition to Industry 5.0. Digital twins mimic and simulate real-world systems and play a crucial role in various industries. XR provides innovative user experiences through virtual reality (VR), augmented reality (AR), and mixed reality (MR). By integrating digital twin simulations into XR devices, these technologies are utilized in various industrial fields. However, the prevalence of XR devices has increased the exposure to cybersecurity threats in ICS and digital twin environments. Because XR devices are connected to networks, the control and production data they process are at risk of being exposed to cyberattackers. Attackers can infiltrate XR devices through malicious code or hacking attacks to take control of the ICS or digital twin or paralyze the system. Therefore, this study emphasizes the cybersecurity threats in the ecosystem of XR devices used in ICSs and conducts research based on digital forensics. It identifies potentially sensitive data and artifacts in XR devices and proposes secure and reliable security response measures in the Industry 5.0 environment.

Co-creating innovations with users: A systematic literature review and future research agenda for project management

This study aimed to systematically review the extensive literature on user innovation co-creation and connect the findings to the project management domain. It focused specifically on new product development, offering a domain-based systematic review of methods, tools, and user types involved in the co-creation process. Analyzing a total of 266 articles, the authors synthesize the types of users and methods discussed in the domain of user innovation, aligning them across the new product development cycle and specific phases of co-innovation. Additionally, the authors formulate research questions and propositions that may inspire the project management domain. This study provides insights into innovation-oriented, exploratory project management and enhances the configuration approach to project management. From a practical perspective, it provides a comprehensive overview of methods that can enrich a managerial toolkit for leading innovative projects.

Co-design knowledge mobilization tools for universal accessibility in municipalities.

Modern research teams are re-evaluating conventional methods with the aim of improving the usefulness of knowledge for users, focusing on the role of knowledge users in shaping innovation. In disability field, encouraging participatory research inherently involves diverse perspectives and inclusion, which aligns with the principles of universal accessibility. By actively involving individuals with various backgrounds, abilities, and needs in the research process, we can better understand and address the challenges faced in adopting universal accessibility. This approach ensures that solutions are more comprehensive, inclusive, and effectively cater to the needs of all individuals, fostering a more equitable and accessible environment for everyone. Despite municipal organizations mandating universal accessibility action plans, they lack tools for efficient implementation. The aim of this study was to develop knowledge mobilization tools tailored to a specific municipal context in Quebec, Canada, to facilitate the implementation of universal accessibility measures by municipal employees. The co-design process employed in this study was organized into four distinct stages, following the Morales model: (1) Exploration (2) Co-Design (3) Validation (4) Development. Stages one and two highlighted the employees' lack of awareness about universal accessibility issues and their need to have more information and resources about how universal accessibility is encountered in their work. A steering committee co-designed three video vignettes about universal accessibility, the city's action plan and measures included in it. The co-design approach used in this study allowed us to observe the non-linear nature of partnership research with an organization as complex as a municipality. Our study shows significant advantages of collaboration between the municipal sector and research.

Automatic depression prediction via cross-modal attention-based multi-modal fusion in social networks

Depression has become a worldwide public health concern in recent years. The online social network can be served as a tool to predict latent depressed users. However, existing studies primarily use machine learning or deep learning methods on multi-modal information with simple concatenation, resulting in unsatisfactory prediction. Additionally, the lack of interpretability in extracted features is a challenge. Furthermore, the majority of these studies primarily concentrate on English social networks. To address these issues, we propose a novel unified multi-tasking training model named CrossAMF (Cross-modal Attention-based Multi-modal Fusion). CrossAMF extracts crucial multi-modal features with explainability and effectively fuses representations of different modalities. Our approach employs a sentiment filtering-based XLNet-CNN-BiGRU model and Reduce-VGGNet to extract textual and image features, respectively. We also introduce innovative user behavior metrics previously unexplored. We collect a dataset of Chinese depressed users from Sina microblog with their texts and images, including 5692 depressed users and 9121 normal users. Experimental results demonstrate the significance of each modality to our task, with the combination yielding the best performance. CrossAMF outperforms other state-of-the-art methods with 0.9097 in accuracy and 0.8915 in F1, showing the potential of application in screening out early depression automatically.

The Beating Heart of Untapped Business Opportunities for Additive Manufacturing

This article presents two cases that join user-driven innovation and additive manufacturing (AM) to examine latent business opportunities for AM in the medical sector. The first case arose as a response to shortages during the early stages of the covid 19 pandemic. The second case, explored in more depth, came from maker-medical collaboration during preparation for a life-threatening operation. Surgeons, confronted with a patient with a delicate heart condition, collaborated with a prototyping facility to print a realistic 3D model of the patient’s aortic aneurysm. The model allowed the surgeons to first study and then experiment to determine the most effective operation procedure before the actual operation, which shortened the surgery time by approximately 70%. Reducing surgery time creates two forms of value: improving patient outcomes and reducing costs. Shorter times under anesthetic and on cardiopulmonary bypass correlate with better surgical results. Reducing healthcare costs brings broad societal benefits in both publicly and privately funded healthcare systems. We outline a case for makerspaces to capture value by joining their expertise and manufacturing equipment with the needs of nearby healthcare systems for novel business development.

Navigating the Regulatory Labyrinth: Compliance Dilemmas and Lead User Innovation in the Fintech Sector

Abstract This research article deals with the lead user innovation difficulties in the Kenyan financial technology sector, specifying the regulatory compliance challenges. The flourishing of fintech firms in diverse aspects and sectors have faced numerous dilemmas, particularly in intellectual property, privacy and consumer safety regulations which may lead to lack of adherence. The consequences of non-compliance can be severe, including legal penalties and reputational damage. Despite the importance of innovation in fintech companies, the dilemmas innovators face in navigating regulatory compliance is not yet fully investigated. This research adopts and employs a sequential mixed-method approach that allows complex connection of lead users and regulators in terms of compliance. Survey data from 321 lead users and in-depth interviews with 36 lead users and five regulators revealed a range of compliance challenges. Intellectual property laws scored the least adherence, with the plethora of regulations and overseeing bodies contributing to increased non-compliance. The outcomes highlight the pressing compliance issues faced by lead users and underscore the potential of regulatory bodies to bolster adherence. The outcomes indicate the need for a different approach to regulatory compliance by lead users. This paper underscores the necessity of cooperative engagement between innovators and regulators to effectively maneuver through the dynamic compliance landscape of the financial technology industry.

Equity principles: Using social theory for more effective social transformation in agricultural research for development

CONTEXTAgricultural innovations and their applications are increasingly recognized as crucial mechanisms for achieving the 2030 Sustainable Development Goals (SDGs). Actors in agricultural research for development (AR4D) frequently use Agricultural Innovation Systems (AIS) frameworks to comprehend the ecosystems within which innovations are developed and scaled. Given the SDGs' emphasis on social outcomes, a reflection on social diversity, power, and the integration of social theory into AIS and AR4D tools is crucial for addressing the nuances of social objectives. OBJECTIVEThis research critically evaluates AIS frameworks and AR4D tools through applying social theory to enhance social outcomes. We offer practical application through the development of “Equity Principles for Social Transformation (EPs).” These EPs are designed to guide AR4D organizations in innovation and scaling efforts that effectively achieve meaningful social outcomes. Through this approach, we aim to enrich the conceptual understanding of equity within AIS and provide practical strategies for implementing these insights, thus empowering AR4D actors to be more effective. METHODSWe start by selecting key social theories to analyze global power imbalances and local social exclusion within AIS frameworks and AR4D tools. Using these theories, we examine three case studies to uncover gaps in their approach to social dimensions. We categorize these gaps through thematic analysis and formulate EPs informed by social theories and a practical understanding of AR4D tools. RESULTS AND CONCLUSIONSEquity analysis of each case study reveals gaps in understanding social implications within upstream and downstream research efforts. These gaps include insufficient addressing of power dynamics and agency recognition, lack of comprehensive guidance on critical social components, oversight of cultural and institutional norms, exacerbation of social inequities, and the case studies' limitations in flexibility for addressing social inclusion effectively. Additionally, there is a notable lack of clear operational guidelines for applying the frameworks in diverse contexts, including the challenge of translating conceptual levels into local action. Seven EPs were developed: recognize AR4D power dynamics; define goals, anti-goals, and for whom; build global “horizontal” partnerships; acknowledge social differences among innovation users and non-users; innovate and curate innovation appropriately; assess impact and reflect; and develop systems capacity. SIGNIFICANCEThe EPs connect innovation systems with positive social change. They help AR4D professionals consider and evaluate the impact of innovation. The EPs provide an additional framework that enables AR4D practitioners to prioritize user needs from the beginning, challenge biases, and more effectively achieve the social objectives outlined in the SDGs.

PReventing and Approaching Crises for frail community-dwelling patients Through Innovative Care (PRACTIC): protocol for an effectiveness cluster randomised controlled trial

BackgroundDemographic changes, with an increasing number and proportion of older people with multimorbidity and frailty, will put more pressure on home care services in municipalities. Frail multimorbid people receiving home care services are at high risk of developing crises, defined as critical challenges and symptoms, which demand immediate and new actions. The crises often result in adverse events, coercive measures, and acute institutionalisation. There is a lack of evidence-based interventions to prevent and resolve crises in community settings.MethodsThis is a participatory action research design (PAR) in a 6-month cluster randomised controlled trial (RCT). The trial will be conducted in 30 municipalities, including 150 frail community-dwelling participants receiving home care services judged by the services to be at risk of developing crisis. Each municipality (cluster) will be randomised to receive either the locally adapted TIME intervention (the intervention group) or care as usual (the control group). The Targeted Interdisciplinary Model for Evaluation and Treatment of Neuropsychiatric Symptoms (TIME) is a manual-based, multicomponent programme that includes a rigorous assessment of the crisis, one or more interdisciplinary case conferences, and the testing and evaluation of customised treatment measures. PAR in combination with an RCT will enhance adaptations of the intervention to the local context and needs. The primary outcome is as follows: difference in change between the intervention and control groups in individual goal achievement to resolve or reduce the challenges of the crises between baseline and 3 months using the PRACTIC Goal Setting Interview (PGSI). Among the secondary outcomes are the difference in change in the PGSI scale at 6 months and in neuropsychiatric symptoms (NPSs), quality of life, distress perceived by professional carers and next of kin, and institutionalisation at 3 and 6 months.DiscussionThrough customised interventions that involve patients, the next of kin, the social context, and health care services, crises may be prevented and resolved. The PReventing and Approaching Crises for frail community-dwelling patients Through Innovative Care (PRACTIC) study will enhance innovation for health professionals, management, and users in the development of new knowledge and a new adapted approach towards crises.Trial registrationClinicalTrials.gov identifier: NCT05651659. Registered 15.12.22.

Next-Gen Medical Technology a Smart Approach to Syringe Injection Pump Automation

This presents the design, implementation, and successful validation of a cutting-edge IoT-based Syringe Injection Pump (SIP) for precision medication administration. In response to the increasing demand for enhanced healthcare automation, this system leverages technologies to address critical challenges in medication delivery. This SIP incorporates a robust Internet of Things (IoT) framework, enabling seamless communication between the device and a central healthcare management system. The automated syringe injection process is governed by a sophisticated algorithm that considers patient-specific parameters, ensuring precise dosage administration. Through extensive testing and real-world simulations, the results demonstrate a significant reduction in human error and improved medication adherence. The system’s architecture integrates secure communication protocols, ensuring data confidentiality and integrity during transmission. An innovative user interface provides healthcare professionals with real-time monitoring and control capabilities, enhancing situational awareness and responsiveness. Furthermore, the SIP’s adaptability to diverse medical environments underscores its versatility in meeting the evolving needs of healthcare institutions. To validate the system’s effectiveness, a comprehensive performance evaluations, including dosage accuracy, response time, and reliability under varying conditions was conducted. Results indicate an impressive dosage precision of 99.8%, showcasing the system’s reliability in critical healthcare scenarios. The IoT connectivity facilitates remote monitoring and control, allowing healthcare providers to intervene promptly in case of anomalies or emergencies. In addition to its technical prowess, the SIP aligns with current healthcare trends by promoting sustainability and cost-effectiveness. The automated system optimizes resource utilization, reduces medication waste, and minimizes the environmental impact associated with traditional manual injection methods. In conclusion, this IoT-based Syringe Injection Pump represents a paradigm shift in medical technology, offering a smart and results-oriented solution for precise medication administration. The successful implementation and validation of this system pave the way for improved patient outcomes, streamlined healthcare workflows, and a more sustainable approach to medication delivery. This research contributes to the ongoing discourse on advancing medical technology and underscores the potential of IoT in shaping the future of healthcare.

Reengineering Indoor Air Quality Monitoring Systems to Improve End-User Experience.

This paper presents an indoor air quality (IAQ) monitoring system designed for a better end-user experience. The monitoring system consists of elements, from the monitoring sensor to the monitoring interface, designed and implemented by the research team, especially for the proposed monitoring system. The monitoring solution is intended for users who live in houses without automatic ventilation systems. The air quality sensor is designed at a minimum cost and complexity to allow multi-zone implementation without significant effort. The user interface uses a spatial graphic representation that facilitates understanding areas with different air quality levels. Presentation of the outdoor air quality level supports the user's decision to ventilate a space. An innovative element of the proposed monitoring interface is the real-time forecast of air quality evolution in each monitored space. The paper describes the implementation of an original monitoring solution (monitoring device, Edge/Cloud management system, innovative user monitoring interface) and presents the results of testing this system in a relevant environment. The research conclusions show the proposed solution's benefits in improving the end-user experience, justified both by the technical results obtained and by the opinion of the users who tested the monitoring system.

The Contemporary Art of Image Search: Iterative User Intent Expansion via Vision-Language Model

Image search is an essential and user-friendly method to explore vast galleries of digital images. However, existing image search methods heavily rely on proximity measurements like tag matching or image similarity, requiring precise user inputs for satisfactory results. To meet the growing demand for a contemporary image search engine that enables accurate comprehension of users' search intentions, we introduce an innovative user intent expansion framework. Our framework leverages visual-language models to parse and compose multi-modal user inputs to provide more accurate and satisfying results. It comprises two-stage processes: 1) a parsing stage that incorporates a language parsing module with large language models to enhance the comprehension of textual inputs, along with a visual parsing module that integrates an interactive segmentation module to swiftly identify detailed visual elements within images; and 2) a logic composition stage that combines multiple user search intents into a unified logic expression for more sophisticated operations in complex searching scenarios. Moreover, the intent expansion framework enables users to perform flexible contextualized interactions with the search results to further specify or adjust their detailed search intents iteratively. We implemented the framework into an image search system for NFT (non-fungible token) search and conducted a user study to evaluate its usability and novel properties. The results indicate that the proposed framework significantly improves users' image search experience. Particularly the parsing and contextualized interactions prove useful in allowing users to express their search intents more accurately and engage in a more enjoyable iterative search experience.

The impact of crowdsourcing and user-driven innovation on R&D departments’ innovation activity: Application of multivariate correspondence analysis

Research background: In enterprise practices, innovation management is taking on more and more open forms. New, creative sources of inspiration are being sought. More and more companies are opening up to cooperation with external people or entities, thus entering a path of open innovation and crowdsourcing. This development is facilitated by increasingly large numbers of online and virtual communities. The idea is to use the potential of the crowd — collective intelligence and creativity. As the strategy is still developing, knowledge in this area is limited. There is a paucity of research on the impact of crowdsourcing on R&D departments and their innovative activities. Purpose of the article: The study aims to determine whether the use of customer support in the form of crowdsourcing affects the innovative activities of R&D departments that implement user-driven innovation (UDI). Methods: An original questionnaire was used for the study. Fifty-seven R&D departments in Poland participated in the research. A correspondence analysis, performed on the basis of the Burt matrix, was applied for the analysis. The authors also used Cramer's V correlation coefficients. Examination of the acquired correlation coefficients reveals the existence of four distinct categories of enterprises regarding the usage of crowdsourcing and implementation of product innovations, completed R&D projects, employment in R&D departments, and percentage of revenue allocating in R&D works. Findings & value added: Research has shown that R&D departments positively evaluate the effects of using UDI in market research analyses of customer purchasing behavior. It helps to create or improve products or services offered on the market, especially in the field of customization, using the information from national research and development units at the same time. Their purpose is mainly to increase the product range. The findings can help academics and practitioners improve the body of knowledge about the determinants of innovation activity, especially concerning relationships with customers and user-driven innovation practices.

Lowland smallholders’ livelihood vulnerability to Climate change-induced hazards in Southern Ethiopia

Livelihood vulnerability to climate change-induced hazards is a serious problem for all agro-ecological contexts, notwithstanding being more severe for various groups of lowland smallholder farmers in Ethiopia. This study used cross-sectional survey data of 422 households from three sublowland agro-ecologies to assess differences in lowland smallholder farmers' vulnerability to climate change-induced hazards. Exposure, sensitivity, and adaptive capacity indications were built based on the literature review. The vulnerability index of the Intergovernmental Panel on Climate Change and the livelihood vulnerability index were calculated by giving different weights through principal component analysis (PCA) to the standardized indicators. The findings show that hot-to-warm sub-moist lowland agro-ecology is highly exposed, and sensitive and also has a lower ability for risk adaptation. This may be due to comparatively limited access to institutional infrastructure, usage of innovation, wealth status, diversification of sources of income, and social networks compared to other lowland agro-ecologies (p < 0.001). The policy implication of the study's findings is that the government and nongovernmental organizations must plan and implement sublowland agro ecology-specific adaptation strategies to reduce vulnerability to climate change-induced hazards by giving priority to the Hot-to-Warm Sub-Moist lowland Area.

Spillover effects of interactions on user innovation: Evidence from a firm-hosted open innovation platform

Firm-hosted open innovation platforms (OIPs) enable multidirectional communication and interaction among users, and they have become a vital IT artifact that absorbs external resources for enterprise innovation. A key challenge for OIPs is how to motivate users’ idea contributions. The support community appears as a Q&A section in a few OIPs, in which the special role of user behavior on individuals’ idea contribution is understudied. Based on a theoretical synthesis of innovation management studies, we propose hypotheses regarding the spillover effects of user interactions in a support community (i.e., help giving and help seeking) on individuals’ innovation performance (i.e., the quantity and quality of ideas). Using a dataset from a typical OIP, we employ two empirical studies to investigate the spillover effects of user interactions and their characteristics, including breadth and depth, on innovation performance. Our results confirm the existence of spillover effects and reveal a positive effect of interaction breadth and a nonlinear effect of interaction depth on innovation. Notably, the nonlinear relationship can be moderated by the interaction breadth. Our findings provide both theoretical and practical implications for user innovation and OIP operations.