How User‐Created‐Content (UCC) Service Quality Influences User Satisfaction and Behaviour

The Internet is undergoing a gradual shift from Web 1.0‐based user interaction to Web 2.0, which has a greater emphasis on user‐created content (UCC) and user collaboration (Hsu & Hsu, 2008). Since existing models of e‐service quality are likely deficient under Web 2.0, we build on them and test a new framework using 319 users who frequented UCC websites. Among other findings, three service elements together explained 44% of the variance in user satisfaction and 33% of the variance in website usage. These elements were: the provider‐user relationship (customization and participation), the relationship among users (e.g., user empowerment), and user compensation. Copyright © 2012 ASAC. Published by John Wiley & Sons, Ltd.     

Team‐based learning and training transfer: a case study of training for the implementation of enterprise resources planning software

While traditional models of training such as behavioral modeling (BMT) have been found to enhance training transfer, research suggests that more active learning strategies such as error management (EMT) and team‐based learning (TBL) may be more effective. This paper analyzes BMT, EMT and TBL strategies to train employees on new enterprise resources planning (ERP) software and discusses which training leads to successful procedural and declarative knowledge transfer, knowledge retention and application, and tangible business outcomes. TBL was predicted to be the most effective training type, as it models several components needed to use ERP software in the actual job setting. Overall and procedural knowledge as well as knowledge application scores improved most for TBL participants, while declarative knowledge improved the most in the EMT condition. During training, all conditions showed significant improvement in knowledge application; however, the TBL condition showed the highest knowledge application gains. This paper discusses the elements of TBL that support its use as an effective strategy to increase knowledge transfer in an organizational context.     

Determinants of Web 2.0 technologies for knowledge sharing in SMEs

Web 2.0 technologies are increasingly being used within all knowledge management processes. This paper extends previous studies on the use of internet technologies and knowledge management by analyzing factors affecting knowledge sharing through Web 2.0 technologies within small and medium-sized enterprises (SMEs). Drawing upon the technology-organization-environment framework, a model is developed to examine how distinct contextual factors influence the use of Web 2.0 technologies for knowledge sharing. A data set of Spanish SMEs is used to test the conceptual model and hypotheses. Results show that knowledge sharing through Web 2.0 technologies emerges from internal organizational and technological resources rather than from external pressure.     

A diagnostic framework for measuring Web‐site localization

This study provides a framework for analyzing the extent of a company's Web localization efforts based on four constructs that capture the overall quality of Web localization: content localization, cultural customization, local gateways, and translation quality. The framework is used to measure Web‐site localization efforts directed toward the U.S. Hispanic online market. The results show that most U.S. Web sites emphasize translation of the Web content from English to Spanish without localizing the site in terms of navigation, graphics, colors, and other culturally relevant content. A scorecard is provided for practitioners to use in assessing and enhancing their companies' Web‐site localization efforts. © 2009 Wiley Periodicals, Inc.     

Social Technologies,Informal Knowledge Practices,and the Enterprise

This article focuses on the ways in which social technologies facilitate informal knowledge sharing in the workplace. Social technologies include both common technologies such as email, phone, and instant messenger and emerging social networking technologies, often known as social media or Web 2.0, such as blogs, wikis, public social networking sites (i.e., Facebook, Twitter, and LinkedIn), enterprise social networking technologies, etc. We know social technologies support informal interactions over digital systems and influence informal social connections among people within and across organizational boundaries. To understand the role of social technologies in informal knowledge practices, we pursue a field study of knowledge workers in consulting firms to investigate the role of social technologies in their informal knowledge sharing practices. Our theorizing from the data is guided by the conceptual premises of sociomateriality to better understand the ways social technologies are integrated with common knowledge practices. Findings highlight five knowledge practices supported by the use of social technologies. Building from these findings we offer conceptual insights regarding the material performance of different social technologies as an assemblage.     

Inductive Regression Tree and Genetic Programming Techniques for Learning User Web Search Preferences

Most Web search engines determine the relevancy of Web pages based on query terms, and a few content filtering applications allow consumers to block objectionable material. However, not many Web search engines and content filtering applications learn the user preferences over time. In this study, we proposed two machine-learning approaches that can be used to learn consumer preferences to identify documents that are most relevant to the consumer. We test the proposed machine learning approaches on a few simulated data sets. The results of our study illustrate that data mining approaches can be used to design intelligent adaptive agents that can select the relevant Web pages, given query terms, for the user.     

Organizational Adoption of Web 2.0 Technologies: An Empirical Analysis

While Web 2.0 technologies such as blogs, wikis, and social networks have been popular in the consumer space, there is significant variation in adoption of Web 2.0 technologies in business. Yet, little is known about why firms adopt Web 2.0 technologies. There is a paucity of empirical research examining the antecedents of the use of Web 2.0 technologies in organizations. Drawing on the Technological-Organizational-Environmental theoretical framework, our study presents and empirically tests a model of factors associated with organizational adoption of Web 2.0 technologies. We find that importance to open standards is positively associated with the propensity for adoption of Web 2.0 technologies. Further, larger organizations are found to have a higher propensity for adoption. Finally, industry knowledge intensity is found to be positively associated with a higher propensity for adoption. Our results suggest that open architectures, firm size, and industry knowledge intensity play pivotal roles in Web 2.0 technology adoption. The study sheds light on antecedents of organizational adoption of Web 2.0 technologies and can help researchers and practitioners build an understanding of what factors are likely to motivate firms to adopt Web 2.0 technologies.     

Internet user behaviour in France and Britain: exploring socio‐spatial disparity among adolescents

The Internet has radically transformed society – although its diffusion has been uneven. Various studies of digital inequality have been undertaken in Anglo‐Saxon communities. Few studies have investigated digital inequality from a socio‐spatial perspective (urban vs. suburban, rather than urban vs. rural) in a French setting. This absence underscores a gap in knowledge and methodology. It highlights the complexities of gathering comparable data on Internet user behaviour beyond national borders. This paper takes a multidisciplinary approach to investigate emerging trends in Internet use across different territories (inner‐city and suburban, as opposed to urban vs. rural) by means of in‐depth interviews with Internet users aged 13–15 years old in France and Britain. The aim is to provide a broad understanding of the way in which teenage Internet users behave online in different territories. The investigation reveals a number of converging trends that are common to both France and Britain and some unexpected disparity.     

Interoperability: Our exciting and terrifying Web3 future

This article introduces the next major generational evolution of the web: Web3. We review the fundamental evolution of the internet and the web over the past 3 decades, including a brief presentation of the publications in Business Horizons that are important in a discussion of the emergence of Web3. We then discuss what these recent developments mean to organizations, consumers, and the public. Though the degree to which Web3 will be widely adopted is uncertain, these technologies are already creating both exhilarating and terrifying implications for e-commerce, digital media, online social networking, online marketplaces, search engines, supply chain management, and finance, among others. We propose the consideration and management of technical, organizational, and regulatory interoperability for Web3 to deliver on its promises of value and that failure to consider these interoperability components may destroy economic value, consumer confidence, or social issues online. We also call on our fellow researchers to focus on these interoperability issues and how they might impact the positive and negative sides of Web3 technologies to help us understand and shape our Web3 future.     

User preference mining based on fine-grained sentiment analysis

User preference mining is an application of data mining that attracts increasing attention. Although most of the existing user preference mining methods achieved significant performance improvement, the sentiment tendencies of users were seldom considered. This paper proposes fine-grained sentiment analysis for preference mining. The powerful feature representation capabilities of deep neural networks have significantly improved the performance of fine-grained sentiment analysis. But two main challenges remain when using deep neural network models: incomplete user feature extraction and insufficient interaction. In response, a pre-training language model is employed to encode user features to fully explore potential interests of users, a linguistic knowledge model is introduced to assist the encoding, a multi-scale convolution neural network is adopted to capture text features at different scales and fully utilize the text information, and the fine-grained sentiment analysis task is modeled as a sequence labeling problem to explore the sentiment polarity of user evaluation. Experiments on a user review data set are used to verify the new approach. Experimental results of precision, recall rate and F1-value show that the proposed approach performs better, and is more effective than baseline models. For example, the F1-value is increased by 4.27% compared to the best performing baseline model. Findings have important implications for research and practice.     

A Qualitative Study of Consumer‐Generated Videos about Daily Deal Web sites

Deal of the day, also known as social couponing, is an e‐commerce business model that offers consumers heavily discounted deals on a regular (daily) basis, and gives merchants access to a mailing list of potential new customers in exchange for a commission. There are thousands of deal Web sites worldwide, offering deals from industries as diverse as hospitality, consumer electronics, fashion, and medical services. This study was performed to learn more about consumers’ attitude toward deal of the day, and their motivations for purchasing (or not purchasing) daily deals. A systematic qualitative methodology called BASIC IDS was used to analyze 30 consumer‐generated YouTube videos about deal Web sites. The analysis showed that many deal‐prone consumers can be considered “deal mavens”; they take effort to learn about different sites and offerings and are eager to share their knowledge with others. Although many of these mavens show hedonistic shopping tendencies, others appear to focus mainly on utility, that is, monetary savings. Consumers with a negative attitude toward deal of the day are often worried about receiving poor service, and some believe that redeeming a deal voucher makes them look cheap.     

Application of the Information Bottleneck method to discover user profiles in a Web store

ABSTRACT

The paper deals with the problem of discovering groups of Web users with similar behavioral patterns on an e-commerce site. We introduce a novel approach to the unsupervised classification of user sessions, based on session attributes related to the user click-stream behavior, to gain insight into characteristics of various user profiles. The approach uses the agglomerative Information Bottleneck (IB) algorithm. Based on log data for a real online store, efficiency of the approach in terms of its ability to differentiate between buying and non-buying sessions was validated, indicating some possible practical applications of the our method. Experiments performed for a number of session samples showed that the method is capable of separating both types of sessions to a large extent. A detailed analysis was performed for the number of clusters ranging from two to seven, and the results were compared to those achieved by applying the most common clustering algorithm, k-means. Increasing the number of clusters generally leads to better results for both algorithms. However, IB demonstrated much higher average efficiency than k-means for the corresponding number of clusters, and this superiority was especially clear for lower number of clusters. The IB-based division of user sessions into seven clusters gives the mean entropy value of 0.28, which means the 95% separation of sessions of both types. Furthermore, a big advantage of our approach is that it gives a possibility to analyze the probability distribution of session attributes in individual clusters, which allows one to discover hidden knowledge about common characteristics of various user profiles and use this knowledge to support managerial decisions.     

Knowing how to use and understand recipes: What arithmetical understanding is needed when students with mild intellectual disabilities use recipes in practical cooking lessons in Home Economics?

The aim of this study was to explore what arithmetical understanding is needed when students with mild intellectual disabilities use recipes during practical cooking lessons in Home Economics. The settings were compulsory schools in Sweden attended by students with intellectual disabilities. Sixteen lessons in Home Economics during which cooking took place were observed. In total, 37 students and three teachers participated. All students had a mild intellectual disability. Their ages varied, but most were between 13 and 14 years old. The sociocultural perspective on learning, combined with a literacy framework, was used as a theoretical foundation for the study. Main findings are that students need an arithmetical understanding of (i) how to interpret numbers, (ii) how to interpret and use units, and (iii) how to compute when using recipes. The knowledge and skills needed to be able to use a recipe are featured in the concept recipe literacy, capturing both theoretical, declarative knowledge and the more practical, procedural knowledge. Recipe literacy can be used to theorize the use of recipes when learning to cook, as in Home Economics.     

Global Social Media Usage: Insights Into Reaching Consumers Worldwide

This study documents global social media usage patterns based on a large‐scale survey of 4,630 social media users around the world. The study provides insights into how users in the European Union, United States, and BRIC (Brazil, Russia, India, and China) regions use social media for business and personal use. It analyzes variability in global social media platforms being used in these different world regions. The study also presents insights into usage of multilingual content for global social media consumption and the global user propensity to translate social media. Finally, the paper showcases an innovative technology solution to help companies leverage machine and human translation to enable users to translate social media content. © 2012 Wiley Periodicals, Inc.     

Strengthening the voice of mental health service users and carers in Wales: a focus group study to inform future policy

Improving the mental health of the people in Wales lies at the heart of the Welsh Assembly Government's public health agenda and the current reforms of the National Health Service in Wales. However, relative to its importance as a health problem, spending on mental health is disproportionately low. Statutory authorities in Wales highlight the importance of listening to, and learning from, service users and carers. This is seen as a way of improving services within the limited funding that is available. The aims of this study were to describe the ways in which mental health service users and carers are currently involved in mental health services across Wales; and to consider the need for an all‐Wales mental health service user and carer ‘national mechanism’ to promote genuine partnership. Eight focus groups were held across Wales attended by mental health service users and carers. There is a clear picture of the level and nature of participation, evidence of good practice and user and carer based aspirations for future participation. There is an untapped source of energy and experience that could help transform mental health services for the good of all. To ignore this would be to miss an opportunity to improve the quality of care for all those dependent upon these services, both patients and carers.     

Conceptual Advances in Consumers’ Semantic and Episodic Brand Memories: A Mixed Methods Exploration

Consumers strongly rely on their memories and experiences during their decision‐making processes. Yet, despite empirical evidence that both semantic and episodic brand memories affect consumer behavior, literature on their distinction and differential impact is scarce. This empirical investigation seeks to reduce this imbalance by enhancing the understanding of these consumer knowledge structures. Using a mixed methods approach including a collage technique and one‐to‐one interviews (N = 118) consisting of open‐ended and closed‐ended (survey) elements and a subsequent content analysis, this research (1) explores differences in memory between brand users and nonusers, (2) evaluates the distinct impact of semantic and episodic memories on brand perceptions, and (3) presents a taxonomy of the principal domains of semantic and episodic brand memories and their implications for brand management. The article concludes by discussing theoretical, methodological, and managerial implications, as well as opening new avenues for future research directed at understanding and managing consumers’ semantic and episodic brand memories.     

Platform quality factors influencing content providers’ loyalty

This study investigates what platform quality factors affect the contents of the loyalty of content providers to support the continued expansion and sustainability of online platforms. It analyses empirically the influence of platform quality on the satisfaction with and loyalty to the service as well as on the platform's ability to secure content providers from a survey of 222 platform users. It confirms five significant findings for platform quality and user loyalty. First, all five factors of SERVQUAL have meaningful effects on platform user satisfaction. Second, factors affecting service quality differ by gender. Third, while male users regard platform technology as most critical, female users are more concerned about platform events and interests. Fourth, female users care more about customer responses than male users do; however, the user interface is the most critical aspect for both genders. Finally, platform quality has a significant impact on satisfaction and loyalty among content providers. It identifies the importance of platform service quality as a factor to increase user (content providers) loyalty on the platform. And it also investigates differences according to user gender by subdividing platform service users and indicates how service quality effects can change according to user characteristics.     

Not all international assignments are created equal: HQ-subsidiary knowledge transfer patterns across types of assignments and types of knowledge

Drawing on 50 semi-structured interviews in a case study of a Belgian multinational and its foreign subsidiary in Poland, we develop new insights into how using different types of international assignments (long-term expatriation, short-term expatriation, short-term inpatriation) allows a HQ-subsidiary dyad to transfer different types of knowledge (declarative, procedural, axiomatic, relational), both from and to HQ, during and after the assignment. We show how each type of assignment acts as a unique knowledge transfer channel, and why it is critical that HQ-subsidiary dyads use an appropriate combination and sequence of international assignments reflecting their specific knowledge transfer needs.     

基于可信度计算的分布式共识合作感知算法

对于分布式的认知无线网络,由于不存在融合中心节点,次级用户节点之间的合作感知往往 采用信息交互的渠道进行,其中一种基于共识合作的感知机制受到广泛的研究,但这种机制 在鲁棒性方面存在一定的缺陷,当恶意节点存在时,其错误信息将影响局部的感知判决结果 ,为此,提出一种基于感知节点可信度的共识合作感知机制。在该机制中,各节点对邻居节 点的可信度进行计算,并把计算出的可信度值发送给其他节点,通过对各节点可信度的累加 计算,最终计算出各节点的可信度,各节点以此决定是否与其邻居节点合作以及如何合作。 仿真结果证明,在恶意节点存在的情况下,该算法在感知性能和收敛速度上都较未改进算法 有不同程度的提升,减轻了不可靠节点对合作感知结果的影响。     

Supporting Technologies and Organizational Practices for the Transfer of Knowledge in Virtual Environments

A field study of a global science/technology company provides evidence of the value of both organizational practices and technology tools for supporting knowledge attainment (the combined tacit and explicit knowledge gained in a focal area – in this study we focus on product knowledge attainment) in virtual environments. We present a three-dimensional typology of knowledge management systems. Method of input, form of content, and how the users accrue the benefit of the knowledge help us to argue that organizational practices and technological tools will have independent positive effects on user knowledge attainment. We find attendance at face-to-face community of practice meetings, use of searchable archives, video-on-demand, and full-text search of video-on-demand all positively predict knowledge attainment. We suggest that organizations develop both organizational practices and technical supports for knowledge transfer. An interview with the video-on-demand vendor gives us the context to discuss issues for the support of tacit knowledge in more virtual environments as well as issues of expertise as it relates to support for formal and informal learning.