Digital Economy. Emerging Technologies and Business Innovation

Past research acknowledged the important role of content marketing strategies in generating traffic and brand’s posts popularity. They have been focused mainly on how these content strategies drive the audience’s response in terms of liking, commenting and sharing brand posts on Facebook. However, the characteristics of relevant content strategies that help to make those actions and the specific consumers’ motivations that are stimulated by each action remain unclear. Our aim in this paper is to develop a conceptual model clarifying the effect of two main content marketing strategies, brand-oriented content and social-oriented content strategy, on generating traffic in social media, through the mediation of consumers’ motivations to create traffic online.

This explorative study is focused on blog readers who read or follow professional and personal blogs. The purpose of this research is to investigate how blog readers perceive and anticipate both blogs in general and professional blogs. In particular, the main interest of the research is to investigate the influence of monetising activities in blogs on authenticity of the blog authors and credibility of their blogs. The insights into the motivations and attitudes of the readers demonstrate the need of best practices on finding the balance between monetisation and self-presentation of the authors in their blogs. This study reveals a few issues that should serve as a motivation for the future research in the field of professional blogging.

Today, to get optimal and effective solutions, firms go toward co-creation and crowdsourcing activities especially the virtual ones. The technological and e-marketing revolutions greatly explain the spread of those collaborative practices. Special interest of this study is on consumer perceptual and behavioral responses toward co-designed packaging in order to assess the worthiness of conducting an online co-design experience. For this reason, based on categorization and regulatory focus theories, we developed a research model to understand consumer’s perceptual and psychological effects on his responses toward co-designed packaging. A cross-cultural study through an online experiment brings to light unpredicted findings and new insights for co-design and consumer psychology literatures, as well as, for e-marketers and professionals.

Social media platforms have engendered new avenues for social participation, which enables non-profit organizations and their core stakeholders to build a fruitful relationship. Yet, emerging challenges have hindered them from taking advantages of all features offered by the new media namely with reference to potential donors’ receptivity to online charitable presence. Therefore, a critical examination of opportunities and challenges associated with nonprofit and donor’ use of these media is needed. Our study examines donors’ receptiveness toward online charitable activities. To achieve this aim, we designed a qualitative study using in-depth individual interviews. Our findings reveals the perceived benefits of the integration of social media in nonprofit’ work and explore barriers that prevent effective use of these platforms in nonprofit practices.

There is a plethora of studies on financial exclusion of the poor, mostly in developing countries. A related but unanswered question is, whether the likelihood of e-banking inclusion and its determinants are similar for the banked and the unbanked. The distinction is important for both the corporate sector and policy makers to answer the question of whether the drivers of e-banking adoption are limited to technological progress. The objective of this paper is to model the likelihood of the banked in a traditional fiat money system (f-banking) to be e-banking included. The Bivariate Probit Sample Selection model is applied with a recent data set from the Kenya Financial Access Household Survey 2015. The results show that there is ninety two percent likelihood of the f-banked to be e-banked. By contrast, the results also show that the absolute financially excluded have seventy six percent probability of being e-banking included. Economic intuition supported by empirical analysis reveals that for an average financially excluded person, it is as a result of persevering over past hardship to be finally e-banking included. The results raise a call to policy makers that the easiness of the f-banked to enter the e-banking market may soon result in e-banking cost sky-rocketing to the detriment of the absolute financially excluded, who have so laboriously tested the e-banking market in the presence of uninsured and unhedged eminent risk.

We investigate the influence of banking development on innovation, including firms that are dependent on external finance. We control, furthermore, the corporate governance impact. Using data from the listed French companies on the SBF 120, we find positive effect of banking development on innovation by financing R&D investments, including firms that are dependent on external finance. Further, when innovation is measured by new patents, the impact of banking development disappear. However, corporate governance seems to affect significantly innovation, including a positive effect of independent outside directors in the board.

The objective of this work is double. On the one hand, it aims at diagnosing the practices of environmental scanning in the start-up companies belonging to the ICT sector in Tunisia, and on the other hand, it aims at counting their real needs in information. Based on questionnaires and interviews, our results show that in spite of the awareness of the importance of competitive intelligence, the latter suffers from several cultural weaknesses (weak information sharing) and material weaknesses (financial and logistic). Our results, particularly demonstrate the pre-eminence of the informal sources of information collection and sharing and the urgent need for the technological scanning, the tenders’ scanning the event scanning. The competitive intelligence remains a recent, poorly developed, and poorly structured, poorly formalized and poorly effective practice. It does not appear among the priorities of the young Tunisian entrepreneurs who grant it a little time.

Several Lightweight cryptosystems were specially designed for constrained-devices. For this reason many papers have been comparing and assessing existing Lightweight cryptosystems. Our contribution; compared to those papers; is to analyse the recently and popular Lightweight cryptosystems using actual devices used in IoT context namely the Raspberry Pi 2 B and Arduino UNO. The evaluation is based on RAM and ROM consumption, speed performance by evaluating Encryption/Decryption time speed and clock cycle and security level. The results of this evaluation indicates the superiority of Speck in term of memory consumption, Rectangle in term of speed performance and Present in term of security level.

In recent years, the interest of using model architectures based on the Convolutional Neural Networks in steganalysis has been rapidly increasing. Regarding the success of deep learning in the field of imaging analysis. Previous approaches have focused on proposing complex architectures with large sizes of images rather than simple models. In this work, we propose a more adjustable flexible architecture with the use of small size images. The robustness of our method is based on using a set of High Pass Filters (HPF) to extract the residual noise on one hand and exploiting the concept of Transfer Learning ensuring the propagation of optimal weights on the other hand. Three state-of-the-art steganographic algorithms in the spatial domain: WOW, S-UNIWARD, and HUGO are used to evaluate the effectiveness of our classification method. Our proposed technique shows an accelerated convergence for the low payloads and provides a better detection accuracy for the high payloads with a classification accuracy rate crossing 96%.

In this paper, we are interested in learning specific probabilistic relational models, named Directed Acyclic Probabilistic Entity Relationship (DAPER) models, from partially structured databases. Algorithms for such a learning task already exist for structured data coming from a relational database. They have been also extended to partially structured data stored in a graph database where the Entity Relationship (ER) schema is first identified from data, and then the DAPER dependency structure is learnt for this specific ER schema. We propose in this work a joint learning from partially structured graph databases where we want to learn at the same time the ER schema and the probabilistic dependencies. The Markov Logic Network (MLN) formalism is an efficient solution for this task. We show with an illustrative example that MLN structure learning can effectively learn both parts of the DAPER model in one single task, with a comparative precision, but with a very high complexity.

In recent years, semantic web technologies and ontologies in particular, are being increasingly used in various e-Health systems and applications. However, issues related to automatically constructing, populating and enriching such ontologies are still outstanding. In this paper, we propose an automatic Adverse Drug Events (ADE) ontology population approach so called ADETermino. The proposed approach is based on Information Extraction methods and mainly aims to extract new concept instances and relationships from textual drug leaflets. It combines a Named-Entity Recognition (NER) system using lexical resources and a machine learning method using a multi-class Support Vector Machine (SVM) classifier for relations detection. Experiments were performed using 102 cardiac drug leaflets corresponding to 5706 input vectors. The results show the performance of our approach with an F-score of 89%.

This work seeks to identify the determinants of e-learning effectiveness. We have measured this effectiveness through three individual variables which are motivation, self effectiveness and anxiety towards technology. The objective is to make it possible to the various concerned actors to better understand the factors influencing e-learning effectiveness. Therefore, the research question is formulated as follow: What are the factors contributing to e-learning effectiveness?

The empirical validation of the model has been carried out through a sample of 350 learners registered in two Tunisian establishments. The empirical validation is ensured by factor analyses and structural equations models. Based on these analyses, we could partially validate the effect of motivation, and computer anxiety on the learners’ reaction. Moreover, we were able to check the important effect of motivation on learning.

Individuals update their knowledge and integrate new one within their professional behavior by training. The literature review revealed a set of variables which affect the acquisition and the realization of skills and knowledge by learners of the virtual school of the post office. In the research, the effectiveness of e-learning experience refers to the realization of learning. Based on the Kirkpatrick’s model, we admit the effect of learner reflexivity, the e-learning system quality and the motivation to learn on the effectiveness of learning on line. The work focuses on these factors and their conceptual and empirical relation with the acquisition and the realization of skills via e-learning. Building on the same perspective, we propose a theoretical model for the purpose to discuss the following question; what are the determinants of the acquisition and realization of learning?

E-government is one of the areas that have been strongly impacted by Information and Communication Technology (ICT) in general and by the growing use of social media, in particular. Social networks are indeed, being increasingly used as an e-participation tool for a better involvement of citizens in decision-making with their governments, raising consequently important and challenging issues, such as the automatic analysis of the massive data generated on the social web. In this paper, we share the findings of a study undertaken on the official Facebook pages of the Tunisian government ministries and governorates, aiming to: (1) shed the light on the way Facebook is being currently used by government institutions, (2) to study the way Tunisian citizens are interacting on this social platform, (3) to pinpoint the specific characteristics of the Tunisian citizen-generated content on the government social pages, which will constitute an essential basis for investigating appropriate techniques and approaches to the Tunisian social web automatic analysis.

Non-communicable diseases such as obesity, diabetes, cardiovascular diseases and cancers have become a major health concern for most countries around the world. Different key elements as social, biological and environmental cause the non-communicable diseases. But the only way that can intentionally modified to avoid these diseases is the motivation to reduce risk factors. Several prevention strategies have been launched worldwide thorough governmental programs by implementing policies/laws. However, these programs don’t integrate active communicate participation and support with the social community. This research aims to first bring out, the priority of enhancing the level of public awareness of Non-Communicable Disease in Tunisia.

This paper focus on the construction of “Sahtek”, a Facebook solution developed on the fundamentals of Social Marketing, to better coach and promotes awareness of Non-Communicable Disease prevention.