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Selecting the right supplier is a critical decision in sustainable supply chain management. Sustainable supplier selection plays an important role in achieving a balance between the three pillars of a sustainable supply chain: economic, environmental, and social. One of the most crucial aspects of running a business in this regard is sustainable supplier selection, and, to this end, an accurate and reliable approach is required. Therefore, the main contribution of this paper is to propose and implement an ontology-based approach for knowledge acquisition from the text for a sustainable supplier selection domain. This approach is dedicated to acquiring complex relationships from texts and coding these in the form of rules. The expected outcome is to enrich the existing domain ontology by these rules to obtain higher relational expressiveness, make reasoning, and produce new knowledge. [ABSTRACT FROM AUTHOR]

Using metocean data, offshore wave height and period are predicted from the wind speed by three state-of-the-art machine learning algorithms (an artificial neural network, a support vector machine, and random forest). Knowledge engineering and data mining are the two biggest pillars of modern intelligent systems. Graph databases are a recent technology that specifically focus on element-driven data browsing rather than on batch processing. Knowledge induction from data is often based on using a wide range of machine learning algorithms and feature selection or extraction algorithms. [Extracted from the article]

Sustainability assessment has received more and more attention from researchers and it offers a large number of opportunities to measure and evaluate the level of its accomplishment. However, proper selection of a particular sustainability assessment approach, reflecting problem properties and the evaluator’s preferences, is a complex and important issue. Due to an existing number of different approaches dedicated to assessing, supporting, or measuring the level of sustainability and their structure oriented on the particular domain usage, problems with accurate matching frequently occur. On the other hand, the efficiency of sustainability assessment depends on the available knowledge of the ongoing capabilities. Additionally, actual research trends confirm that knowledge engineering gives a method to handle domain knowledge practically and effectively. Unfortunately, literature studies confirm that there is a lack of knowledge systematization in the sustainability assessment domain, however. The practical application of knowledge-based mechanisms may cover this gap. In this paper, we provide formal, practical and technological guidance to a knowledge management-based approach to sustainability assessment. We propose ontology as a form of knowledge conceptualization and using knowledge engineering, we make gathered knowledge publicly available and reusable, especially in terms of interoperability of collected knowledge. [ABSTRACT FROM AUTHOR]

In recent years, conducted businesses have been increasingly expected to obtain more sustainable forms, with many added determinants. Indeed, sustainability-related entrepreneurship still faces complex choices among conventional entrepreneurial factors, while being urged to consider three main pillars of sustainability. Thus, this work is focused on the development of sustainability-related entrepreneurship by reflecting the sustainable needs of entrepreneurship. Due to the fact that it is not clear for the sustainability-related entrepreneurship what the valuable and most influential factors stimming its development are, the detection of basic components and their correlation becomes a major motivation of this work. Therefore, this paper aims to conduct an attempt to identify a comprehensive set of SE (sustainable entrepreneurship) factors providing a structural overview in making insights into the factors/determinants of SE. It assists researchers and entrepreneurs in obtaining clear, informative pictures about SE factors. The applied research methodology is based on a systematic literature review which is conducted using the PRISMA methodology, simultaneously ensuring repetitiveness and lack of bias in this process. To retrieve and condense the immense amount of bibliographic information, a bibliometric analysis is adopted to perform in co-occurrence analysis of keywords determining SE factors and different detailed forms of distribution analysis. The expected outcome is to provide the classification schema of applied keywords in sustainable entrepreneurship literature as part of a comprehensive literature review, which is presented in order to uncover, classify and systematize the current research. As a result, a co-word matrix of high frequency keywords of SE factors is also established. It offers a feasible path of investigation for researchers aiming to build a consistent body of knowledge about sustainable entrepreneurship, by providing a conceptualization and systematization that can be applied across the many contexts in which sustainable entrepreneurship is expressed, for example, sustainable actions and sustainable development contexts. The present research aims to yield a successful attempt of identifying the comprehensive set of SE factors, as well as to establish a co-word matrix of high frequency keywords of SE factors. Providing a macroscopic overview of the main factors of SE in the form of conceptualization of the proposed construct will capture the unique organizational characteristics of sustainable enterprises and facilitate the research into capability building, innovation and competitive advantage in sustainable enterprises. It supports both researchers and entrepreneurs in shaping up and refining future research activities and investments in line with the policy of SE. [ABSTRACT FROM AUTHOR]

The supplier selection problem is one of the most important competitive challenges used by modern enterprises. Due to the fact that companies have to improve their practices in the management of a green supply chain that aims to respect green practices and technologies to increase sustainability, selecting the optimal green supplier is a challenging multi-dimensional problem. While most of the research has focused on the development and improvement of new methods, relatively limited attention has been paid to the identifying sets of criteria and capturing the domain knowledge. This issue is significant because a correctly identified set of criteria plays a vital role in supporting the decision-making process. The approach presented creates a gap between classical assumption of decision making and knowledge-based problem structuring. The current paper presents a methodological and practical background for capturing and handling knowledge about green supplier selection criteria, supported by a formal guideline for their appropriate acquisition. In addressing this research challenge, the aims of this paper are twofold: providing meta-analysis to reveal a collection of key data supported by a formal and trustworthy bibliometric analysis, and capturing knowledge in one place in the form of ontology for enabling selection and evaluation criteria of green suppliers is proposed. The proposed ontology is available for public use. [ABSTRACT FROM AUTHOR]