Iranian Journal of Information Processing & Management
Year:2020 | Volume:36 | Issue:1 (103)|Papers Count:10

One of the key success factors in the journey to digitalization is to cultivate and develop a new generation of leaders called “ digital leaders” . Given the importance of this issue in the present era, researchers have addressed this role in many aspects as one of the essential factors determining the success of organizations in the digital age. However, the fundamental issue is what is the status of studies on digital leader’ s role in terms of both structural and contextual perspectives? This is important because, to date, relevant researches have focused less on providing a complete picture of researches in this area. Accordingly, in response to this challenge, this research intends to provide a comprehensive view of the international conducted studies in the field of digital leader’ s role. In order to achieve this, the qualitative meta-analysis was used to examine and analyze 46 studies in the field which each of them had a different perspective and methodology. For that purpose, we follow a structured and iterative process built on Okoli & Schabram’ s guidelines and Fink’ s approach to search, identify, and analyze the relevant literature. Finally, in order to evaluate the results of structural and contextual analysis, the peer debriefing strategy were used. The results showed that all conducted researches have predominant features both structurally and contextually. In this regard, in the structural perspective, “ time distribution of studies, the method of data collection, the industry distribution of studies and the type of researcher participation” were evaluated. In the contextual perspective, based on the thematic synthesis, five main research themes including “ drivers of role definition, goals and objectives, functions, role structure and role competencies” in the field of digital leader’ s role were identified and finally, thematic network of the concepts and issues related to each area were drawn up. From the contextual point of view, results of this study showed that over recent years the number and quality of articles have increased, as well as the research focus has expanded to various dimensions; So that in 2019, all five areas of this role have been addressed in numerous studies. Overall, the findings of this article provide a basis for understanding the different research aspects in the field of digital leader’ s role. It also provides a framework to design and develop researches in the field of digital leader’ s role.

In this study, a theme analysis conducted to identify effective factor for engaging user to academic social network. Use and gratification theory was used as theoretical foundation for the study. To do this, in-depth interviews was conducted with 20 Research Gate user. Findings showed that seven factors include of communication, promotion of professional knowledge and identity, information seeking, awareness, social engagement, collaboration establishment as well as value creation, are affecting user engagement in Research Gate. Finding also indicated that users primarily seek information to enhance their professional identity; then they engage and use the Research Gate network in order to enrich their knowledge and professional identity, increase their academic collaborations, social engagements and communications with other researchers in their scientific community.

The present survey aims to study the scientific texts and social texts linked each other by citations in order to investigate the influence of scientific terms on social texts. The social text is expected to be a bridge between scholars and users by citing scientific texts. By indexing scientific and social text and measuring its similarity by means of an inclusion index, it is possible to see the influence of scientific terms on social texts. The basis of the statistical data of the present study is the scientific papers on climate change issues published in the journals covered by the Web of Science, which have the role of the research community. Sample members consisted of 9876 scientific and social texts (7912 social texts cited 1964 scientific texts) that were extracted and stored in. txt files with the help of Python web scraping using beautiful soup package. The pdf files were extracted manually and converted to a. txt file. The indexed terms of the scientific and social texts and the common terms between them, were identified and categorized according to their length and document types separately using the automatic negative indexing model and regular expressions. Measuring the penetration of scientific terms on social texts using the inclusion index showed that the average penetration rate was 27%. There was a positive, significant and strong correlation (0. 76) between the number of common terms and academic penetration. The results of chi-square test showed that there is a significant relationship at 1% level between the term length and the average penetration rate. There is also a difference between the level of penetration and the type of social documents type, including news, blogs, policy documents, Wikipedia, and peer reviews. The highest percentage of penetration is related to policy documents and then Wikipedia. Obtaining 22 citations and 40 social citations on average per paper, and the strong correlation between citation and altmetric score, indicates the citation influence among the academic and non-academic community. Collectively, with the power of altmetrics like policy documents, Wikipedia and blogs and their permeability, they can be used to further promote scientific findings. Publishing scientific findings in these sources, even in a different language from scientific authors, can contribute to greater awareness of society and the general public.

Reporting research limitations in academic literature is very important for understanding and utilizing research findings. This study aims to assess the extent to which and how research limitations acknowledged in Persian theses and dissertations (TDs). 664 Persian TDs published from 2009 to 2018 selected randomly through cluster sampling technique from IranDoc’ s TDs database and the last chapter of 578 TDs analyzed. Through content analysis method, reported limitations analyzed and coded. Around 17% of TDs (99/578) addressed at least one limitation in their reports, while 64% of them had a specific heading for this section. The trend of reporting limitations has increased during current decades and students in humanities areas have paid more attentions to this section. Overall, 22 key limitations have been repeated 268 times in the TDs and “ sampling bias” is more frequent with 29 repeats among them. Addressing research limitations in TDs is very incomplete. Transparent addressing of research limitations may help readers and stakeholders understand and apply research findings more effectively. The role of educators and academic institutes to inform newcomer researchers about the importance and structure of research limitations section in their reports is vital. This is the first study to examine research limitations in Persian academic literature and can inspire more research on this subject. The stakeholders of research, such as faculties, students, universities, research centers, readers/beneficiaries, and sponsors will be informed about key research limitations in TDs.

The important role of cognitive biases aspects at different stages of information retrieval is mentioned in most information retrieval models. So, it is necessary to understand cognitive aspects of behavior and human interaction. Since cognitive biases is one of effective cognitive aspects in information searching and users experience them, the effect of these biases should be considered. Therefore, the purpose of this study is to investigate the role of demographic variables in frequency of cognitive biases in information retrieval. The method of this study is survey, and in terms of purpose this is an applied research implemented in combined method (qualitative and quantitative). The research population was graduate students of Ferdowsi University (humanities students and engineering students) studying at this university in second semester, 1397-1398. In this research, data were collected using stratified sampling method. The required data for this research was gathered based on log file and semi-structured interviews that were based on check list of different cognitive biases. The content validity of interview questions was evaluated by KIS and psychology specialists and the reliability of both instruments is also correlated with the coefficient of agreement between the opinions of two evaluators that was 0. 95. The results showed that in the cognitive biases, including “ anchoring” , “ attention” and “ mere exposure” , there was a significant difference between the frequency of these biases occurrences in users based on gender. Also, in the cognitive biases, including “ overconfidence” , “ recency” , “ attention” and “ availability” , there was a significant difference between the frequency of these biases occurrences in users based on grade (M. A. and PhD). Other findings showed that in the cognitive biases, including “ reency” and “ attention” , there was a significant difference between the frequency of these biases occurrences in users based on the field of study (humanities and engineering). Based on the findings of this research, it can be concluded that designers of information retrieval systems and librarians should pay attention to the demographic variables (gender, degree and field of study) in designing and evaluating information systems because these variables can affect frequency of some biases occurrences in information searching. Of course, the impact of factors like age group, character types, mental schemas, culture and information literacy rate should not be overlooked.

Knowledge is an important part of any organization’ s asset and the most important sources of knowledge is related to customers. Hence, companies use knowledge management in order to increase their competitive advantage, and in particular try to benefit from the customer knowledge as the major factor in the organization success. This research aims to analyse the effect of customer knowledge on organizational performance through new product development in IT industry using System Dynamics approach. For this purpose, initially, the literature was reviewed and, based on interviews with experts and analyzing the interviews using grounded theory the model variables were identified, relationships were determined, and the dynamical modeling of the the causal diagram was drawn. The results of this study provide a dynamic model showing that knowledge and customer knowledge affect the product development, financial performance, customer numbers, idea numbers, customer loyalty, the time from idea to launch the product, and internal processes. Besides, it was found that to increase the impact of cstomer knowledge on the company performance, knowledge maturity is essential. This research can be useful both in terms of the research approach used and the results for different fields of engineering.

Cloud computing as a computing infrastructure provides powerful solutions for data storage, processing, and distribution, and can easily and quickly integrate, adapt, and deploy enterprise-wide enterprise platforms and reduce usage and maintenance costs. Organizational architecture is an integrated approach that provides comprehensive solutions for designing and deploying different dimensions of the organization. Providing a combination of cloud computing and enterprise architecture can provide a model for the deployment and applications of cloud computing and explain how actors play a role in deploying this technology. This study has tried to provide a proposed framework for taking advantage of both technologies in the field of human resource management based on the “ TOGAF” architectural model by analyzing the convergence of organizational architecture and cloud computing. This research, using a meta-synthesis method analyzes literature on cloud computing models and architectures, organization architecture, and human resource management. After identifying 19 concepts in five main categories, the organizational architecture model is based on providing the cloud and extending its application to the task of human resource management. The validity of the model was evaluated and validated by the experts and the Lawshe model. Based on findings, in developed model the components, steps, activities and outcomes of the framework are presented and described. The proposed framework model has three main roles: the consumer business, the provider of cloud-based business services, and the developer and vendor of the cloud service. Cloud computing has been adapted to the layers of enterprise architecture and its applications are presented.

Recent researches show that Data is one of the most valuable and important assets of organizations and businesses. Privacy in the dissemination of data is becoming increasingly challenging. Anonymity as one of the privacy strategies on one side, conceals the relationship between individuals and records in a metadata table and on the other side, preserves the usefulness of the data for subsequent analysis. Preventing information disclosure becomes difficult when the adversary possesses background knowledge. We propose an anonymization framework to protect against background knowledge attack, identity disclosure, and feature disclosure. The anonymization algorithm creates equivalence classes of records whose probability distributions extracted by background knowledge are similar. Our proposed algorithm satisfies k-anonymity and its extension too. The proposed anonymity algorithm tries to satisfy the privacy model while preserving the usefulness of the anonymous data. We verify the theoretical study by experimentation on two datasets. Experimental results show that our proposed algorithm outperforms the state of the art anonymization approaches in terms of loss of information.

The aim of this research is to comprehensively investigate various types of Data-Driven Business Patterns in order to help entrepreneurship and innovation actors, especially digital businesses efforts. This paper is a critical-argumentative study using a narrative review with a documentary approach. In order to collect and extract information, a comprehensive search was carried out on documents in the Iranian international scientific journals databases and some of the most famous management consulting groups in the world. The statistical population of this study was all documents related to the keyword Data-Driven Business Model in the period 2000 to 2018. After studying documents, in the literature section, 26 patterns of Data-Driven Business Model were indexed. After analyzing similarities, 20 patterns were counted. In the second review of these cases, 13 different patterns were identified, and in the third review period, the necessity of the need for these 13 patterns was identified by 5 complementary tools. Data-driven business model patterns can help innovators and entrepreneurs utilize the patterns in proportion to their customer groups or even think of the world’ s most successful businesses using these patterns. In this study, for the first time, all types of data-driven business models were collected from different perspectives. If companies want to actually use these patterns, they should also be equipped with a set of complementary tools. Major complementary tools play a role in data ethics, identification of data stakeholders, and business-data alignment.

The aim of this study is to design an ontology-based electronics learning system. The present research is a descriptive research in terms of its purpose and methodology. In the present study, to explore the main concepts of the field of e-learning, we reviewed the published articles and sources of information on e-learning. Finally, the main categories of e-learning areas including human resources, technology infrastructure, and educational content were identified. In the present study, the basis of the method used to extract semantic concepts and relationships, the knowledge engineering approach, and the basis of the method used to create ontology is top-down method. Proté gé software 3. 5 was also used to build an ontology. In this study, seven stages were used to construct ontology, including determining the scope and ontology coverage, determining the ontology hierarchy, determining the conceptual pairs, determining the classes, describing the characteristics, defining the quarries and creating the sample. According to the results of the study, the proposed method can be used to complete and develop the proposed ontology for e-learning.