共查询到12条相似文献，搜索用时 28 毫秒
1.
In the past few decades, much research has documented the importance of users as sources of innovations. Over the last 10 years, Research Policy alone has published 56 research articles investigating this phenomenon. We ask to what degree the findings of users as innovators have been absorbed by decision-makers responsible for new product development (managers) and by those who shape the contextual conditions for innovation (policy makers and public administration). A realistic perception of the sources of innovation is important as it constitutes the basis for a rational allocation of resources and thus indirectly impacts the innovation performance of companies and societies at large.In a large-scale survey of n?=?1500 decision-makers, we found support for a substantial underestimation of users as a source of innovation: While the true proportion of user innovation among the most valuable 1678 innovations in nine industries is 54.4% (as established in existing research articles), decision-makers estimate it to be 21.7%. A content analysis of transfer media (450 academic textbooks, popular innovation books, and business articles) underscores this theory-practice gap: Of 3469 text paragraphs dealing with the sources of innovation, only 2.7% mention users as innovators. We develop six propositions on the reasons for and consequences of this underestimation that may serve as a starting point for future research and practical consequences. 相似文献
2.
《International Journal of Information Management》2016,36(4):653-667
This study examines the effects of user experience on user resistance to change—particularly, on the relationship between user resistance to change and its antecedents (i.e. switching costs and perceived value) in the context of the voice user interface of an in-vehicle infotainment (IVI) system. This research offers several salient findings. First, it shows that user experience positively moderates the relationship between uncertainty costs (one type of switching cost) and user resistance. It also negatively moderates the association between perceived value and user resistance. Second, the research test results demonstrate that users with a high degree of prior experience with the voice user interface of other smart devices exhibit low user resistance to change to the voice user interface in an IVI system. Third, we show that three types of switching costs (transition costs, in particular) may directly influence users to resist a change to the voice user interface. Fourth, our test results empirically demonstrate that both switching costs and perceived value affect user resistance to change in the context of an IVI system, which differs from the traditional IS research setting (i.e. enterprise systems). These findings may guide not only platform leaders in designing user interfaces, user experiences, and marketing strategies, but also firms that want to defend themselves from platform envelopment while devising defensive strategies in platform and standards competition. 相似文献
3.
Algorithms are progressively transforming human experience, especially, the interaction with businesses, governments, education, and entertainment. As a result, people are growingly seeing the outside world, in a sense, through the lens of algorithms. Despite the importance of algorithmic experience (AX), few studies had been devoted to investigating the nature and processes through which users perceive and actualize the potential for algorithm affordance. This study proposes the Algorithm Acceptance Model to conceptualize the notion of AX as part of the analytic framework for human-algorithm interaction. It then tests how AX shapes the satisfaction with and acceptance of algorithm services. The results show that AX is inherently related to human understanding of fairness, transparency, and other conventional components of user-experience, indicating the heuristic roles of transparency and fairness regarding their underlying relations of user experience and trust. AX can influence the user perception of algorithmic systems in the context of algorithm ecology, offering useful insights into the design of human-centered algorithm systems. The findings provide initial and robust support for the proposed Algorithm Acceptance Model. 相似文献
4.
《Research Policy》2023,52(7):104791
This paper introduces a newly digitized, open-access version of the Food and Drug Administration’s “Orange Book”—a linkage between approved small-molecule drugs and the patents that protect them. The Orange Book also reports any applicable regulatory exclusivity that prevents competitive entry. We summarize the Orange Book’s coverage and discuss the opportunities and challenges associated with using these data for research. Empirical validations against various administrative datasets suggest that Orange Book records are, largely, complete and accurate. We conclude with a specific use case—calculating legal exclusivity periods for drugs—to highlight the types of choices that researchers must make when using this resource. 相似文献
5.
Wouter P.C. BoonAuthor Vitae Ellen H.M. Moors Author VitaeStefan Kuhlmann Author Vitae Ruud E.H.M. Smits Author Vitae 《Research Policy》2011,40(2):242-252
User involvement is assumed to be beneficial to innovation processes. Intermediary user organisations contribute to articulating societal demands for innovations. However, the learning processes inside these organisations are still not understood well. Therefore, this paper empirically investigates intermediaries using an event history approach. It yields characteristic learning mechanisms, e.g. concerning the management of expectations or actively building a case. If intermediaries overcome challenges regarding positioning, representation and the level of proactivity, they can play a precarious role in demand articulation in the context of new technologies. 相似文献
6.
《Information processing & management》2023,60(5):103456
To achieve personalized recommendations, the recommender system selects the items that users may like by learning the collected user–item interaction data. However, the acquisition and use of data usually form a feedback loop, which leads to recommender systems suffering from popularity bias. To solve this problem, we propose a novel dual disentanglement of user–item interaction for recommendation with causal embedding (DDCE). Different from the existing work, our innovation is we take into account double-end popularity bias from the user-side and the item-side. Firstly, we perform a causal analysis of the reasons for user–item interaction and obtain the causal embedding representation of each part according to the analysis results. Secondly, on the item-side, we consider the influence of item attributes on popularity to improve the reliability of the item popularity. Then, on the user-side, we consider the effect of the time series when obtaining users’ interest. We model the contrastive learning task to disentangle users’ long–short-term interests, which avoids the bias of long–short-term interests overlapping, and use the attention mechanism to realize the dynamic integration of users’ long–short-term interests. Finally, we realize the disentanglement of user–item interaction reasons by decoupling user interest and item popularity. We experiment on two real-world datasets (Douban Movie and KuaiRec) to verify the significance of DDCE, the average improvement of DDCE in three evaluation metrics (NDCG, HR, and Recall) compared to the state-of-the-art model are 5.1106% and 4.1277% (MF as the backbone), 3.8256% and 3.2790% (LightGCN as the backbone), respectively. 相似文献
7.
There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able
to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why
a system is secure. In both cases, an important goal of explanation is to acquire or maintain the users’ trust. In this paper,
I investigate the relation between explanation and trust in the context of computing science. This analysis draws on literature
study and concept analysis, using elements from system theory as well as actor-network theory. I apply the conceptual framework
to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main
focus is on expert systems (AI) and electronic voting systems (security). Finally, I discuss consequences of the analysis
for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities. 相似文献
8.
9.
《International Journal of Information Management》2017,37(5):367-379
The primary aim of this study is to examine the factors that predict end users’ intention to adopt mobile government (m-government) services in a developing country. The research is based upon a self-administered questionnaire survey of 120 current users’ in the United Arab Emirates (UAE), a leader in m-government development in the Arab world. The study employs advanced statistical techniques to test an extended the Technology Acceptance Model (TAM) by incorporating the determinants of trust, cost, social influence, variety of services, perceived usefulness in information technology and demographic profiles. The findings revealed that trust and social influence are positively associated with end users intention to adopt m-government services in the UAE. By identifying the predictors of users’ adoption of m-government, this study provides several theoretical and practical implications related to m-government service adoption. 相似文献
10.
《Information processing & management》2022,59(2):102869
User-created automation applets to connect IoT devices and applications have become popular and widely available. Exploring those applets enables us to grasp the patterns of how users are utilizing and maximizing the power of connection by themselves, which can deliver practical implications for IoT service design. This study builds an IoT application network with the data of the IFTTT(if this then that) platform which is the most popular platform for self-automation of IoT services. The trigger-action relationships of the IFTTT applets currently activated are collected and used to construct an IoT application network whose nodes are IoT service channels, and links represent their connections. The constructed IoT network is then embedded by the node2vec technique, an algorithmic framework for representational learning of nodes in networks. Clustering the embedded nodes produces the four clusters of IoT usage patterns: Smart Home, Activity Tracking, Information Digest, and Lifelogging & Sharing. We also predict the IoT application network using node2vec-based link prediction with several machine learning classifiers to identify promising connections between IoT applications. Feasible service scenarios are then generated from predicted links between IoT applications. The findings and the proposed approach can offer IoT service providers practical implications for enhancing user experiences and developing new services. 相似文献
11.
《Information processing & management》2022,59(6):103108
Our research attempts to track the role of coolness factors (i.e., attractiveness, subculture, and uniqueness) on user satisfaction and loyalty with respect to technological products. For this purpose, we construct a model for a particular technological product on the basis of coolness and satisfaction–loyalty theories. We then gather survey-based data from 454 Koreans for measuring the coolness factors, satisfaction, and loyalty variables. Subsequently, we employ an artificial neural network–structural equation model for testing the proposed model. Based on the outcomes, (1) we find that attractiveness and uniqueness have notable and positive effects on satisfaction, (2) whereas, subculture does not have a considerable impact on satisfaction. (3) In addition, a positive association between satisfaction and loyalty is identified. (4) Interestingly, there are no significant moderating influences of age and gender on the associations of coolness elements. Overall, the outcomes of our research contribute to the expansion of the literature regarding coolness theory and user experience of technologies. 相似文献
12.
With the increasing provenance of hedonic and social information systems, systems are observed to employ other forms of feedback and design than purely informational in order to increase user engagement and motivation. Three principle classes of motivational design pursuing user engagement have become increasingly established; gamification, quantified-self and social networking. This study investigates how the perceived prominence of these three design classes in users’ use of information system facilitate experiences of affective, informational and social feedback as well as user’s perceived benefits from a system and their continued use intentions. We employ survey data (N = 167) gathered from users of HeiaHeia; an exercise encouragement system that employs features belonging to the three design classes. The results indicate that gamification is positively associated with experiences of affective feedback, quantified-self with experiences of both affective and informational feedback and social networking with experiences of social feedback. Experiences of affective feedback are further strongly associated with user perceived benefits and continued use intentions, whereas experiences of informational feedback are only associated with continued use intentions. Experiences of social feedback had no significant relationship with neither. The findings provide practical insights into how systems can be designed to facilitate different types of feedback that increases users’ engagement, benefits and intentions to continue the use of a system. 相似文献