Purpose This paper aims to identify the impact of demographical and organizational variables such as age, gender, experiences use of knowledge management system (KMS), education and job level on knowledge sharing (KS) performance of knowledge workers in knowledge activities of a KMS. Specifically, it seeks to explore that is there any relationship between the KS behavior patterns of high KS performance knowledge workers with their performance. Furthermore, this study using its conceptual attitude model aims to show that whether knowledge workers’ behavior patterns in sharing information and knowledge throughout a KMS have any specific effect or not. Design/methodology/approach This paper proposed a framework to mine knowledge workers’ raw data using data mining techniques such as clustering and association rules mining. Also, this research uses a case-based approach to a knowledge-intensive company in Iran that works in the field of information technology with 730 numbers of workers. Findings Findings suggest that demographical and organizational variables such as age, education and experience use of KMS have positive effects on knowledge worker’s KS behavior in KMSs. In fact, people who have lower age, higher education degrees and more experience use of KMS, have more participation in KS in KMS. Also, results depict that the experienced use of KMS has the most impact on the intention of KS in this KMS. Findings emphasize on the importance of the influence of the behavioral, organizational environments and psychological factors such as reward system, top management support, openness and trust, on KS performance of knowledge workers in the KMS. In fact, according to data, the KMS reward system caused to increasing participation of the users in KS, also in each knowledge activity that top managers participate in, the scores were higher. Practical implications This research helps top managers in designing policies and strategies to improve the participation of knowledge workers in KS and helps human resource managers to improve their membership policies. Also, assist Information Technology (IT) managers to enhance KMSs’ design to leverage with organization strategies in the field of improving KS and encourage people to participate in KMS. Originality/value This research has two key values. First, this paper applies a data mining framework to mining and analyzing data and this paper uses actual data of a KMS in a specialist company in Iran, with about 27,740 real data points. Second, this paper investigates the impact of demographical and organizational attributes on KS behavior, which little is empirically known about the impact of demographical variables on KS intention.

PurposeThis study aimed to present a model for open-data management for developing innovative information flow in Iranian knowledge-based companies (businesses).Design/methodology/approachThe method was mixed (qualitative-quantitative) and data collection tools were interview and questionnaire. The qualitative part was done to identify the influential components in open data management (ecosystem) using the grounded theory method. A questionnaire was developed based on the results of the qualitative section and the theoretical foundations, and the quantitative section was conducted by analytical survey method and the model was extracted using factor analysis and the integration of the qualitative section.FindingsSeven categories of entrepreneurial incentives, sustainable value, innovative features, challenges and barriers, actors, business model and requirements are the main categories that should be considered in open data management (ecosystem) with all categories of research have a significant relationship with open data management.Originality/valueThe study focused on open data management from an innovation paradigm perspective and its role in developing innovative information flow. The study aimed to identify the key components of the open data ecosystem, open-data value creation, and the need to use the “open data” approach to develop data-driven and knowledge-based businesses in Iran–an emerging approach largely ignored.

No abstract

No abstract

No abstract

Numerous studies have been conducted to identify the effects of natural crises on supply chain performance. Conventional analysis methods are based on either manual filter methods or data-driven methods. The manual filter methods suffer from validation problems due to sampling limitations, and data-driven methods suffer from the nature of crisis data which are vague and complex. This study aims to present an intelligent analysis model to automatically identify the effects of natural crises such as the COVID-19 pandemic on the supply chain through metadata generated on social media. This paper presents a thematic analysis framework to extract knowledge under user steering. This framework uses a text-mining approach, including co-occurrence term analysis and knowledge map construction. As a case study to approve our proposed model, we retrieved, cleaned, and analyzed 1024 online textual reports on supply chain crises published during the COVID-19 pandemic in 2019-2021. We conducted a thematic analysis of the collected data and achieved a knowledge map on the impact of the COVID-19 crisis on the supply chain. The resultant knowledge map consists of five main areas (and related sub-areas), including (1) food retail, (2) food services, (3) manufacturing, (4) consumers, and (5) logistics. We checked and validated the analytical results with some field experts. This experiment achieved 53 crisis knowledge propositions classified from 25,272 sentences with 631,799 terms and 31,864 unique terms using just three user-system interaction steps, which shows the model's high performance. The results lead us to conclude that the proposed model could be used effectively and efficiently as a decision support system, especially for crises in the supply chain analysis.

The knowledge sharing creates a collaborative environment which contributes to creation of flexibility and meeting demands in supply chain. It guarantees the access of members to external knowledge and overall supply chain improvement in competitive environment. The steel industry as the second “key” and “strategic” industry after oil and petrochemical industry in Iran as one of the important countries in middle-east and due to its importance for development but also due to the characteristics of its cost accounting system is selected as case study. Regarding to, this study aimed to design a comprehensive list containing all knowledge sharing (KS) motivational factors for steel industries supply chain. Thus, a mixed method of qualitative (a three-phase Delphi method) and quantitative (decision-making trial and evaluation laboratory-DEMATEL) has been adopted. At first stage, the 33 motivational factors of KS were identified through literature review. Then using Delphi method, respondents were provided with the findings from the literature to shortlist and merge the factors based on steel industry supply chain features. Due to different theoretical and practical standpoints of views about KS motivators in steel industry supply chain, 30 respondents (experts) participated. The final factors extracted via Delphi method was 15. Then, DEMATEL method was used to find interdependence among factors. At the end, cost accounting system for each factor were asked from knowledge management departments in steel supply chain. The results indicated that majority of the costs in steel industry supply chain is spent in decreasing power and sense of ownership of knowledge, improving culture and expectations, and improving personal contact and interaction, team culture, rewards, strategic thinking, and individual management of time, respectively. Whereas, the results of DEMATEL technique indicated that team culture, power, and sense of ownership of knowledge; personal contact and interaction; trust; culture; and expectations are the 5th high ranking factors. Although there are plenty of techniques used for improving team culture such as community of practice, after action review, Knowledge caf’e, it is not so dominant in cost accounting system. Hopefully, departments consider power and sense of ownership of knowledge more carefully. Managers in steel supply chain pay more attention to cultural issues by having educational courses. Strategic thinking is not among the highest-ranking factors, but there are costs spent for it in steel supply chain which should be pondered upon it.

No abstract