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The purpose of this paper is to present a new concept – task affordance in crowdsourcing context, and build it as a theoretical lens to help the authors reconfigure the artifacts and process in task-oriented crowdsourcing projects. The paper differs from previous studies by focusing on the relationships between the task artifacts, systems and goal-directed actors in crowdsourcing process rather than on the pure examination of task properties.

An operational definition of task affordance was proposed and a pseudo-entity-relationship model based approach was employed to portrait the task affordance in online crowdsourcing context. Furthermore, the authors developed a typology of task affordance and decomposed the concept into five dimensions, namely, design affordance, presentation affordance, assignment affordance, task-platform fit affordance, and task-worker fit affordance. A preliminary analysis of task affordances across various crowdsourcing categories was also conducted to validate the proposed typological framework.

The findings show that the task affordances have varying degree and extend among the diverse crowdsourcing categories. For instance, task design affordances seem to be low in the crowd processing and crowd rating cases compared with that in the crowd solving and crowd creation cases. For another example, in terms of the task presentation affordance, crowd rating cases need the lowest affordance while the crowd creation cases need the highest affordance. Therefore, the authors would like to emphasize that the successful adoption, implementation, and design of the task-oriented crowdsourcing owes to the careful examination of the relationships among the actors, artifacts, and environment of the crowdsourcing projects.

To the authors’ best knowledge, this paper is the first study on conceptualizing the task affordance in online crowdsourcing context. The study contributes to the academic literature on a comprehensive overview of task-related studies in crowdsourcing, which are scattered in several information related fields. Furthermore, this research contributes directly to the area of information science and technology due to a common interest in studying the environments and contexts in which people, information and technology interact and interplay. Practically, this study may yield some implications for the requester and platform operator when designing the relevant tasks or developing the specific crowdsourcing platform.

The purpose of this paper is to investigate the impact of system-generated visual feedback and continued contribution on individuals’ motivation to share knowledge in a crowdsourcing environment.

An experimental setting was designed to investigate participants’ motivation to contribute knowledge in a crowdsourcing environment. Responses from a total of 101 participants were analyzed. The independent variables were visual feedback and time. The dependent variable was the participants’ self-expressed willingness to further contribute in the experimental knowledge-sharing activity.

A significant main effect of time was found, showing overall gains in the mean willingness to participate over time. It was also found that the mean willingness of the control and top assimilation groups were higher than the mean willingness of the rank contrast and status groups. The mean difference obtained for the control group was mainly during the first half of the knowledge-sharing tasks, while the mean difference obtained for the top assimilation group was mainly during the second half of the knowledge-sharing tasks.

This study contributes to the literature related to motivation in knowledge sharing by providing theory-based, empirical evidence of the potential for external interventions to improve willingness to contribute and sustain knowledge sharing. The findings additionally provide practical implications for motivating and sustaining knowledge sharing.

The purpose of this paper is to theoretically develop the concept of perceived affordance based on the existing studies, and to construct a conceptual framework to show how perceived affordances can facilitate the interaction design of social media.

The paper provides a review of the relevant literature on affordance and perceived affordance, and conceptually proposes a typology of perceived affordances in social media and an integrative framework for interaction design from sociomateriality perspective. Furthermore, a brief empirical example on the interaction design of crowdsourcing systems is used to ground and illustrate the authors' conceptual framework.

The paper shows that the perceived affordances may have multi‐facet characteristics and the interaction design of social media should reflect the multi‐dimensional perceived affordances. The perceived affordances can support or facilitate the design of basic elements of social media, such as content and form, to enhance both usability (human‐computer interaction) and sociability (human‐human interaction). A position of constitutive entanglement does not privilege either users or social media artifacts, nor does it provide a rigid triangle among these three components. Instead, the perceived affordances play a critical role in integrating the key components in social media interaction design as an ensemble.

The paper attempts to explore and develop the concept of perceived affordance and employ it as a theoretical lens to underpin interaction design of social media. Overall, the authors' study contributes to the design science literature in the information management field by elaborating a new theoretical perspective and providing a conceptual framework for the researchers and designers.

In organizations, knowledge intensive activities are mainly task oriented. Finding relevant completed tasks to the new task and providing task-related knowledge to workers facilitate the knowledge reuse. However, relevant tasks are not easily found in the huge amount of completed tasks. The purpose of this paper is to assist the worker to find the required knowledge for the task at hand by reusing the knowledge related to relevant competed tasks.

First, the task profile is constructed. Relevant degrees to categories which tasks to are derived by multi-granularity fuzzy linguistic method. The stages of completed tasks are identified by the modified KNN method. Second, similar completed tasks on categories are retrieved and then the relevant tasks are selected from the retrieved similar tasks by multi-granularity fuzzy linguistic method. Third, the worker’s current task stage is derived by calculating the similarity between the rated knowledge and the knowledge in the stage of completed tasks. Finally, the knowledge is recommend based on stage relevance, relevance of the completed tasks and importance of the knowledge.

The proposed method helps the worker find the knowledge related to the task at hand by finding and reusing the completed tasks. The experimental results show that the proposed method performs well and can fulfill the worker’s’ knowledge needs. The use of the linguistic term set with preferred granularities instead of precise numbers facilitates the expression of the opinions. The recommendation stage by stage makes the knowledge recommended more precisely. The obtained linguistic weight of the knowledge makes the recommended results understood more easily than the numerical values.

In the study, the authors just focus on the codified knowledge recommendation. However, there is another kind of knowledge named tacit knowledge, which exists in the mind of the experts. The constructing and updating of the expert profile can be investigated. Meanwhile, the new recommendation method which considers more factors also needs to be studied further.

The paper includes implications for the development of the knowledge management system. The proposed approach can be applied as a tool of knowledge sharing. It facilitates the finding of the knowledge that is related to the task at hand.

The paper provides new ways to find the relevant tasks and the related knowledge to the task at hand. Meanwhile, the new method to recommend the knowledge stage by stage is also proposed. It expands the research in the knowledge sharing and knowledge recommendation.

The rapid development of Web 2.0 and social media enables the rise of crowdsourcing. Crowdsourcing contest is a typical case of crowdsourcing and has been adopted by many organisations for business solution and decision making. From a participant's perspective, it is interesting to explore what motivates people to participate in crowdsourcing contest. The purpose of this paper is to investigate the category of motivation based on self-determination theory and synthesises various motivation factors in crowdsourcing contest. Meanwhile, perceived motivational affordances and task granularity are also examined as the moderate constructs.

The paper builds a conceptual model to illustrate the relationships between various motivations (extrinsic and intrinsic) and participation effort under the moderating of perceived motivational affordances and task granularity. An empirical study is conducted to test the research model by surveying the Chinese participants of crowdsourcing contest.

The results show that various motivations might play different roles in relating to participation effort expended in the crowdsourcing contest. Moreover, task granularity may positively moderate the relationship between external motivation and participation effort. The results also show that supporting of a participant's perceived motivational affordances might strengthen the relationship between the individual's motivation with an internal focus (intrinsic, integrated, identified and introjected motivation) and participation effort.

Overall, the research has some conceptual and theoretical implications to the literature. This study synthesises various motivation factors identified by previous studies in crowdsourcing projects or communities as a form of motivation spectrum, namely external, introjected, identified, integrated and intrinsic motivation, which contributes to the motivation literatures. Meanwhile, the findings indicate that various motivations might play different roles in relating to participation effort expended in the crowdsourcing contest. Also, the study theoretically extends the crowdsourcing participation research to incorporate the effects of perceived motivational affordances in crowdsourcing contest. In addition, the study may yield some practical implications for sponsors, managers and designers in crowdsourcing contest.

The purpose of this paper is to propose general parallelism techniques for holistic twig join algorithms to process queries against Extensible Markup Language (XML) databases on a multi‐core system.

The parallelism techniques comprised data and task parallelism. As for data parallelism, the paper adopted the stream‐based partitioning for XML to partition XML data as the basis of parallelism on multiple CPU cores. The XML data partitioning was performed in two levels. The first level was to create buckets for creating data independence and balancing loads among CPU cores; each bucket was assigned onto a CPU core. Within each bucket, the second level of XML data partitioning was performed to create finer partitions for providing finer parallelism. Each CPU core performed the holistic twig join algorithm on each finer partition of its own in parallel with other CPU cores. In task parallelism, the holistic twig join algorithm was decomposed into two main tasks, which were pipelined to create parallelism. The first task adopted the data parallelism technique and their outputs were transferred to the second task periodically. Since data transfers incurred overheads, the size of each data transfer needed to be estimated cautiously for achieving optimal performance.

The data and task parallelism techniques contribute to good performance especially for queries having complex structures and/or higher values of query selectivity. The performance of data parallelism can be further improved by task parallelism. Significant performance improvement is attained by queries having higher selectivity because more outputs computed by the second task is performed in parallel with the first task.

The proposed parallelism techniques primarily deals with executing a single long‐running query for intra‐query parallelism, partitioning XML data on‐the‐fly, and allocating partitions on CPU cores statically. During the parallel execution, presumably there are no such dynamic XML data updates.

The effectiveness of the proposed parallel holistic twig joins relies fundamentally on some system parameter values that can be obtained from a benchmark of the system platform.

The paper proposes novel techniques to increase parallelism by combining techniques of data and task parallelism for achieving high performance. To the best of the author's knowledge, this is the first paper of parallelizing the holistic twig join algorithms on a multi‐core system.

Recent years have witnessed the development of a variety of rating systems but the authors have little knowledge about their impact on users’ perceptions of information quality, cognitive decision effort, and enjoyment. The purpose of this paper is to understand the potential cognitive fit underlining the relationship between rating systems types (i.e. five-star, binary-visual, and binary-textual) and tasks (i.e. purchase-decision and browsing tasks) in the context of shopping websites.

A total of 191 subjects were obtained. This study conducted an experiment with a 2×3 between-subject factorial design. The first dimension is a task that has two conditions (purchasing vs browsing). The second dimension is a type of rating system that has three different types (binary-textual, binary-visual, and five-star).

The results show that the cognitive fit may occur when individuals use a five-star rating system to help them make a purchasing decision and when they use a binary-visual rating system while browsing. This fit might increase perceived information quality while decrease cognitive decision efforts, and in turn raise intention to adopt the systems. Moreover, five-star rating systems can make users feel more fun and enjoyment than binary-textual and visual rating systems, regardless of task type.

This study focuses on three main rating systems that are popular on shopping websites. Nevertheless, few other rating systems exist in the market such as unitary or ten-star rating systems. Further studies can consider other types of rating systems and address, in addition to representation, the issue of information granularity (i.e. unitary, binary, five-star, and ten-star rating systems).

The results of this study could provide design principles for web designers in determining which rating systems best match the websites they are developing. If the websites or specific webpages are more utilitarian oriented (hedonic oriented), five-star rating systems (binary-visual rating systems) are more appropriate.

This study contributes to the rating system literature by examining the cognitive fit underlining the relationship between rating systems types and tasks. Importantly, this study extends cognitive fit theory by considering affective responses, that is, perceived enjoyment and intention to continue to use.

The contemporary workplace is characterized by transience: Organizational members frequently turn over and careers span multiple organizations. Consequently, workplace friendships that were once close become less close and intimate, that is they become peripheral and can deteriorate. While research has examined the benefits for employees who move on to new opportunities, less clear is how stayers, or employees who remain behind in the work setting, are affected. To understand stayers’ experiences and how they manage, we draw on theories of belongingess and to offer a three-part episodic process model, which explains how stayers’ engagement in the task and social domains are influenced. In doing so, we (1) present a dynamic view of the deterioration of dyadic relationships, highlighting how workplace relationships can change over time; (2) discuss both the depth and breadth of emotions involved for stayers; and (3) integrate a positive organizational scholarship perspective by considering both strength of friendships with other present coworkers and coping approaches of stayers as important boundary conditions, which can facilitate their recovery process. We draw attention to the broader implications of our theorizing for research on relationships and emotions, and practical implications for management.

In the Web 2.0 era, more and more digital immigrants actively participate in blogging, video sharing, online rating, and micro blogging, etc. However, some may be more skilled in producing and generating online content while others still meet some barriers in doing so. Thus, it is interesting to investigate the online generative capability of digital immigrants in Web 2.0 context. This paper seeks to address this issue.

The authors selected Shanghai as their target province in this study for its large scale of internet users. An in-depth semi-structured interview was used as their research method. They selected several community clubs as the interview settings. In addition, age was adopted as a threshold to define the Chinese digital immigrants for its convenience in sampling.

Chinese digital immigrants are playing an important role in content generating, and have a great potential in the future contribution, and a number of digital immigrants regard the content generating as a pretty easy work while some others felt difficulties, even frustrated and exhausted when generating content. About the content type, digital immigrants prefer to generate that content with low granularity. About the motivation, the intrinsic motivation and the extrinsic motivation with an internalized focus play a dominant role. About the generating mode, digital immigrants prefer to generate content individually or collectively.

This paper develops the concept of online generative capability by adapting the notion of generativity from other disciplines to the characteristics of Web 2.0. Then an integrated conceptual framework is built and evaluated. Practically, the paper puts forward some implications for the designers, managers, and information service staff from different perspectives to facilitate the digital immigrant's online generative capability.

Applies a parallel backward‐chaining technique to a rule‐based expert system on a shared‐memory multiprocessor system. The condition for a processor to split up its search tree (task‐node) and generate new OR nodes is based on the level in the goal tree at which the task‐node is found. The results indicate satisfactory speed‐up performance for a small number of processors (< 10) and a reasonably large number of rules.