The conducted study focused on a multinational ITC (Information Technology and Communications) company. Empirical research aimed to evaluate organizational culture based on Denison’s model through four features: capacity development, basic values, customer orientation, and goals and objectives. At the same time, the study analyzed service provided to customers, taking into account its three phases: pre-transaction, transaction, and post-transaction. As research methods, we used a questionnaire-based survey and direct observation. The results of the study demonstrate that the company has a strong culture based on an adequate core value system (shared by company members), innovative and effective human capital management practices, and customer orientation. All characteristics ensure the integration of sustainability principles into strategies, policies, and management practices of the company. At the same time, the authors develop a design and analysis model of the impact of organizational culture features on customer service effectiveness, highlighting that the four organizational culture features are good predictors for improving customer service effectiveness, which promotes an ethical business model and sustainable pursuit of economic, social and environmental performance. The study identified a set of good management practices and solutions in the design, operationalization, and monitoring of customer service.

This paper presents a sentiment analysis solution on tweets using Recurrent Neural Networks (RNNs). The method is can classifying tweets with an 80.74% accuracy rate, considering a binary task, after experimenting with 20 different design approaches. The solution integrates an attention mechanism aiming to enhance the network, with a two-way localization system: at memory cell level and at network level. We present an in-depth literature review for Twitter sentiment analysis and the building blocks that grounded the design decisions of our solution, employed as a core classification component within a sentiment indicator of the SynergyCrowds platform.

Industrial Organization, the Resource-Based View, and the Relational View are some classical, well-established, and widely accepted theories in the strategic management domain regarding the understanding, explanation, and prediction of competitive advantage of firms and above-average firm performance. Recent evidence of economic geography and regional economics added to this stream of research new perspectives like cluster theory and microeconomic competitiveness. Despite the high enthusiasm with which companies and policymakers embraced the new advancements, there is some contradictory evidence regarding the positive effect of local conditions on firm performance. Thus, in this paper, we aim to empirically test some aspects of a modern regional development theory, proposed mainly by Michael Porter and collaborators, and the impact of these aspects on firm performance. External determinants considered at three levels of analysis (local economy, local clusters, and industry) will be investigated in relation to firm performance. We will analyze empirical data through detailed correlational analyses and by building multilinear regression models. After the statistical analysis of the answers provided directly by 67 medium and large manufacturing companies operating in Romania, we will provide empirical support for some external determinants, while for other determinants, we will show that the data rejected the proposed associations. The main conclusion derived from this study is that different combinations of external determinants, considered at all three levels of analysis, have a positive and significant effect on different measures of firm performance. The findings in our paper are important for both regional economics and the strategic management literature, suggesting the importance of creating local or urban conditions depending on the type of performance that the firms in the local economy are underperforming.