Purpose -The aim of this paper is to develop a theoretical model that enables us to examine the antecedents and consequences effects of members' helping behavior in online communities. It also aims to develop a complete model for empirical testing. Design/methodology/approach -The sample is 425 participants including nine online communities in Taiwan, including Yahoo! Kimo, CPB, Sony music, etc.. who were contacted and asked to participate in the study. Data were collected between August and December 2007 via the web for Internet users using a standardized questionnaire. Excluding those surveys that were undeliverable and those who believed that it was inappropriate to respond, the overall effective response rate was 84 percent (355 of 425). Findings -The empirical results suggested that online communities members' helping behavior represents a large pool of product know-how. They seem to be a promising source of innovation capabilities for new product development.Research limitations/implications -The research only aims to experimentally investigate complete model of helping behavior in online communities. But this research has not dealt with a double role of online communities' members so far, linking innovation with commercialization. They seem to be a promising source of innovation capabilities for new product development. Practical implications -The phenomenon of helping behavior among members may become a major source and channel for information in the decision making process for the purchase of products. Therefore, a major finding derived from the empirical application is that community members are capable and willing to contribute to virtual co-development. Originality/value -Many variables have been evaluated for their influences on the helping behaviors of the members of the online communities. However, none of the previous studies have integrated these variables into a more comprehensive framework.

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The main aim of this paper is to show how green supply chain (SC) environmental sustainability orientation and strategic alliance learning coevolve over time. Our position is that the level of interfirm learning is a determinant of the formations and mastery mechanisms evolving in a green SC. Therefore, this study discusses the environmental sustainability of the learning processes of firms’ alliances during the life cycle of the alliances. This is done in order to encourage firms to follow green innovation and green SCs through enhancing their environmental performance and increasing their competitive advantage in the global market. In addition, this study develops a research structure and test hypotheses on the basis of survey data from 342 Taiwanese firms listed on the stock market. The results indicate that green knowledge acquisition plays a prominent role in the performance of firms’ alliances, especially when implemented in a green SC management (SCM) context. Moreover, according to one of the main findings, as companies evolve through the different phases of the alliance life cycle, their situation shows high potential for creating knowledge sharing through their exploration capabilities. Finally, when firms focus their internal organizations on learning and environmental requirements, they become better able to expand their learning capacity as well as to build and maintain a sustainable competitive advantage.

Healthcare information systems have been dominated by cloud technology and the Internet of Things (IoT) for decades today. In some urgent scenarios, we reveal a prevailing architectural framework that is based on fog/edge optimal computing approaches smart in-home remote healthcare solutions and architectures and recognize the challenges and requirements of IoHT devices for diverse utilization instances. Even with these upsides, conventional centralized access constraint confronts privacy problems and patient health data security. This study likewise constructs a “blockchain-enabled edge that computes” mechanism, through which smart contracts with the consensus protocol produced by Edge Intelligent Server are deployed to secure privacy topics and balance scalability in trustless surroundings. We expect this paper to be a significant guideline for the subsequent elaboration of fog/edge-based systems that compute solutions for smart in-home remote healthcare IoT applications. There will be a change of paradigm from “hospital-based” to “distributed patient in-home healthcare”.