PRODUCT PORTFOLIO ANALYSIS - ARTHUR D. LITTLE MATRIX

In recent decades we have witnessed an unseen dynamism among companies, which is explained by their desire to engage in more activities that provide a high level of development and diversification. Thus, as companies are diversifying more and more, their managers confront a number of challenges arising from the management of resources for the product portfolio and the low level of resources with which companies can identify, at a time. Responding to these challenges, over time were developed a series of analytical product portfolio methods through which managers can balance the sources of cash flows from the multiple products and also can identify the place and role of products, in strategic terms, within the product portfolio. In order to identify these methods the authors of the present paper have conducted a desk research in order to analyze the strategic marketing and management literature of the last 2 decades. Widely were studied a series of methods that are presented in the marketing and management literature as the main instruments used within the product portfolio strategic planning process. Among these methods we focused on the Arthur D. Little matrix. Thus the present paper has the purpose to outline the characteristics and strategic implications of the ADL matrix within a companyâ€(tm)s product portfolio. After conducting this analysis we have found that restricting the product portfolio analysis to the A.D.L. matrix is not a very wise decision. The A.D.L. matrix among with other marketing tools of product portfolio analysis have some advantages and disadvantages and is trying to provide, at a time, a specific diagnosis of a companyâ€(tm)s product portfolio. Therefore, the recommendation for the Romanian managers consists in a combined use of a wide range of tools and techniques for product portfolio analysis. This leads to a better understanding of the whole mix of product markets, included in portfolio analysis, the strategic position held by each product within a market, the performance potential of product portfolio and the financial aspects related to the resource allocation process for the products within the portfolio. It should also be noted that the tools and techniques specific to product portfolio analysis do not give accurate answers, despite the appearances created by the analysis stage, where the products are plotted rigorously. However, their main virtue is simplicity, as these highlight the managersâ€(tm) need for further investigations.product portfolio, ADL matrix, life cycle, competitive position, strategic analysis

THE PREMISES OF STRATEGIC MARKETING PLANNING IMPLEMENTATION WITHIN SMALL AND MEDIUM SIZED ENTERPRISES

The main purpose of the present paper is to identify the framework and the necessary conditions for the small and medium sized enterprises (SMEs) to be able to adopt the strategic marketing planning. Also, the paper aims to underline the importance of the strategic marketing planning and the manner in which the SMEs can adopt, implement and operationalize the strategic marketing planning instruments, whose correct understanding and usage ensure the capacity to generate competitive advantage, the key element both from the perspective of the fierce competition and the perspective of the future development of the SMEs. Within SMEs the implementation of marketing becomes an evident requirment, mostly due to the relationship that these have with the market, thus, leading towards market orientation of the activities, a new approach developed by the marketing vision on managing the activities from these types of organizations. Regarded upon, from the marketing perspective, the activities from the SMEs, especially the marketing activities, cannot take place randomly. Resource allocation, a characteristic of these types of organizations, and the objectives with regards to superior customer needs satisfaction and economic efficiency maximization, claim thorough plannification and deployment of the activities in a sequence that represents the implementation of a strategy previously assumed. Within this framework, the strategic marketing planning appears as a complex process employing all scientific instruments that comprise segmentation, positioning and marketing mix. Utilizing the strategic marketing planning within SMEs depends to further extend on marketing integration; process directly related with a series of factors such as the nature of the market, development stage, product type, management quality and the influences of the marketing department of the SME. The implications onto the marketing activities from SMEs are reflected upon each strategic marketing planning instrument, where we can find, under correct understanding and application, objectives and market and penetration strategies as product, price, distribution and promotion strategies.marketing, SMEs, segmentation, positioning, marketing mix

Cascaded Cross-Modal Transformer for Request and Complaint Detection

We propose a novel cascaded cross-modal transformer (CCMT) that combines speech and text transcripts to detect customer requests and complaints in phone conversations. Our approach leverages a multimodal paradigm by transcribing the speech using automatic speech recognition (ASR) models and translating the transcripts into different languages. Subsequently, we combine language-specific BERT-based models with Wav2Vec2.0 audio features in a novel cascaded cross-attention transformer model. We apply our system to the Requests Sub-Challenge of the ACM Multimedia 2023 Computational Paralinguistics Challenge, reaching unweighted average recalls (UAR) of 65.41% and 85.87% for the complaint and request classes, respectively.Comment: Accepted at ACMMM 202

Social Impact of Psychological Research on Well-Being Shared in Social Media

The purpose of this article is to demonstrate how the Social Impact in Social Media (SISM, hereinafter) methodology applied in psychological research provides evidence for the visibility of the social impact of the research. This article helps researchers become aware of whether and how their improvements are capturing the interest of citizens and how citizens are applying such evidence and obtaining better outcomes, in this case, in relation to well-being. In addition, citizens can access the latest evidence on social media and act as channels of communication between science and social or personal networks and, in doing so, they can improve the living conditions of others. This methodology is also useful for agencies that support researchers in psychology with financial assistance, which can use it to evaluate the social impact of the funds that they invest in research. In this article, the 10 studies on well-being were selected for analysis using the following criteria: their research results led to demonstrable improvement in well-being, and these improvements are presented on social media. We applied the social impact coverage ratio to identify the percentage of the social impact shared in social media in relation to the total amount of social media data collected. Finally, examples of quantitative and qualitative evidence of the social impact of the research on well-being are presented

Social impact of psychological research on well-being shared in social media

The purpose of this article is to demonstrate how the Social Impact in Social Media (SISM, hereinafter) methodology applied in psychological research provides evidence for the visibility of the social impact of the research. This article helps researchers become aware of whether and how their improvements are capturing the interest of citizens and how citizens are applying such evidence and obtaining better outcomes, in this case, in relation to well-being. In addition, citizens can access the latest evidence on social media and act as channels of communication between science and social or personal networks and, in doing so, they can improve the living conditions of others. This methodology is also useful for agencies that support researchers in psychology with financial assistance, which can use it to evaluate the social impact of the funds that they invest in research. In this article, the 10 studies on well-being were selected for analysis using the following criteria: their research results led to demonstrable improvement in well-being, and these improvements are presented on social media. We applied the social impact coverage ratio to identify the percentage of the social impact shared in social media in relation to the total amount of social media data collected. Finally, examples of quantitative and qualitative evidence of the social impact of the research on well-being are presented

CL-MAE: Curriculum-Learned Masked Autoencoders

Masked image modeling has been demonstrated as a powerful pretext task for generating robust representations that can be effectively generalized across multiple downstream tasks. Typically, this approach involves randomly masking patches (tokens) in input images, with the masking strategy remaining unchanged during training. In this paper, we propose a curriculum learning approach that updates the masking strategy to continually increase the complexity of the self-supervised reconstruction task. We conjecture that, by gradually increasing the task complexity, the model can learn more sophisticated and transferable representations. To facilitate this, we introduce a novel learnable masking module that possesses the capability to generate masks of different complexities, and integrate the proposed module into masked autoencoders (MAE). Our module is jointly trained with the MAE, while adjusting its behavior during training, transitioning from a partner to the MAE (optimizing the same reconstruction loss) to an adversary (optimizing the opposite loss), while passing through a neutral state. The transition between these behaviors is smooth, being regulated by a factor that is multiplied with the reconstruction loss of the masking module. The resulting training procedure generates an easy-to-hard curriculum. We train our Curriculum-Learned Masked Autoencoder (CL-MAE) on ImageNet and show that it exhibits superior representation learning capabilities compared to MAE. The empirical results on five downstream tasks confirm our conjecture, demonstrating that curriculum learning can be successfully used to self-supervise masked autoencoders

BodyNet: Volumetric Inference of 3D Human Body Shapes

Human shape estimation is an important task for video editing, animation and fashion industry. Predicting 3D human body shape from natural images, however, is highly challenging due to factors such as variation in human bodies, clothing and viewpoint. Prior methods addressing this problem typically attempt to fit parametric body models with certain priors on pose and shape. In this work we argue for an alternative representation and propose BodyNet, a neural network for direct inference of volumetric body shape from a single image. BodyNet is an end-to-end trainable network that benefits from (i) a volumetric 3D loss, (ii) a multi-view re-projection loss, and (iii) intermediate supervision of 2D pose, 2D body part segmentation, and 3D pose. Each of them results in performance improvement as demonstrated by our experiments. To evaluate the method, we fit the SMPL model to our network output and show state-of-the-art results on the SURREAL and Unite the People datasets, outperforming recent approaches. Besides achieving state-of-the-art performance, our method also enables volumetric body-part segmentation.Comment: Appears in: European Conference on Computer Vision 2018 (ECCV 2018). 27 page