1,723,010 research outputs found
Al-enhanced SaaS marketing: accelerating product-market fit and scaling in the B2B landscape
No full textThis thesis investigates how adaptive and localised artificial intelligence (AI) marketing tools can enhance Kalmar’s outreach efficiency and customer engagement for its software-as-a-service (SaaS) product, MyKalmar Insight, in the context of fragmented media markets and budgetary constraints. Kalmar, a global leader in cargo handling solutions, has evolved from an equipment manufacturer to a digital services provider. It's MyKalmar Insight platform, which delivers machine performance data analytics through a subscription model, represents a strategic shift towards service-based value creation in industrial markets.
Despite growing its machine subscriptions from approximately 1,000 to 4,500 in four years, Kalmar’s marketing challenges. Include low platform engagement; only around 15% of users actively access Insight, and difficulties in reaching the correct decision makers across regions with different languages, cultures, along with digital maturity levels. Given the company’s annual marketing budget of around €100,000, there is a clear need for efficiency-oriented approaches that maximise return on marketing investment.
The thesis explores how AI-enabled adaptive and localised marketing strategies can overcome these challenges. By combining literature on SaaS marketing, AI-driven personalisation with organisational alignment, it argues that adaptive AI systems, such as predictive lead scoring, dynamic content localisation, and intelligent campaign optimisation, can significantly improve Kalmar’s ability to engage global B2B audiences. In addition, it looks at internal alignment between marketing and the product teams as a means of facilitating AI adoption by ensuring that there is consistency in communication with shared performance metrics.
The findings from the study indicate that AI can enable Kalmar to automate multilingual marketing, prioritise high-value customer segments, and personalise outreach without proportionally increasing costs. The study concludes that phased pilot implementations, starting with adaptive content translation and predictive audience targeting, along with cross-functional dashboards, can generate measurable performance improvements while strengthening internal collaboration. Ultimately, the integration of adaptive and localised AI marketing tools offers Kalmar a path to expand MyKalmar Insight’s reach, along with solidifying its digital market leadership under practical financial limits
Replication Data for: Economic Actors as Human Rights Watchers: The Effects of Government Sexual Violence on Foreign Direct Investment
No full textDataset and do file for replication of main analyses in the text
A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals
Full text linkScholarly data is growing continuously containing information about the
articles from a plethora of venues including conferences, journals, etc. Many
initiatives have been taken to make scholarly data available as Knowledge
Graphs (KGs). These efforts to standardize these data and make them accessible
have also led to many challenges such as exploration of scholarly articles,
ambiguous authors, etc. This study more specifically targets the problem of
Author Name Disambiguation (AND) on Scholarly KGs and presents a novel
framework, Literally Author Name Disambiguation (LAND), which utilizes
Knowledge Graph Embeddings (KGEs) using multimodal literal information
generated from these KGs. This framework is based on three components: 1)
Multimodal KGEs, 2) A blocking procedure, and finally, 3) Hierarchical
Agglomerative Clustering. Extensive experiments have been conducted on two
newly created KGs: (i) KG containing information from Scientometrics Journal
from 1978 onwards (OC-782K), and (ii) a KG extracted from a well-known
benchmark for AND provided by AMiner (AMiner-534K). The results show that our
proposed architecture outperforms our baselines of 8-14% in terms of the F1
score and shows competitive performances on a challenging benchmark such as
AMiner. The code and the datasets are publicly available through Github:
https://github.com/sntcristian/and-kge and
Zenodo:https://doi.org/10.5281/zenodo.6309855 respectively
Effects of Water Drinking Test on Ocular Blood Flow Waveform Parameters: A Laser Speckle Flowgraphy Study
No full textPONE-D-16-11516R6
Effects of Water Drinking Test on Ocular Blood Flow Waveform Parameters: A Laser Speckle Flowgraphy Stud
Effects of Water Drinking Test on Ocular Blood Flow Waveform Parameters: A Laser Speckle Flowgraphy Study
No full textPONE-D-16-11516R6
Effects of Water Drinking Test on Ocular Blood Flow Waveform Parameters: A Laser Speckle Flowgraphy Stud
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Development and validation of a knowledge quality instrument for e-learning content / Mehwish Waheed
No full textThis study presents a conceptual and operational measurement of knowledge quality by exploring and understanding the knowledge quality phenomena in existing literature and by identifying the student’s perspective on knowledge quality in the eLearning environment. This further assists in developing a measurement instrument for knowledge quality. The following research objectives have guided the research process: i) explore the dimensions that meet the demand of quality knowledge based on epistemological belief; ii) identify students’ perception about the key dimensions of knowledge quality in eLearning context; iii) examine the influential relationship between knowledge quality and student satisfaction and its subsequent effect on student’s attitudinal loyalty and learning outcomes in terms of perceived academic performance and perceived learning effectiveness.
To achieve the stipulated purpose of this study, a sequential Mixed Method design is opted. Qualitative and quantitative research method has guided this study for knowledge quality instrument development and also in investigating its relationship with student satisfaction, student attitudinal loyalty and learning outcomes. University of Malaya's eLearning environment i.e. SPECTRUM (Student Powered e-Collaboration Transforming UM) is selected as the learning platform that is used in this study for developing knowledge quality instrument.
Open-ended questionnaires were used for qualitative data collection to understand and explore the knowledge quality characteristics perceived by students using eLearning environment (SPECTRUM). Based on analysis of these dimensions from grounded data and verification with existing dimensions in the literature, a 34 items survey instrument was generated for quantitative data collection and empirical testing of the knowledge quality measurement instrument. The final knowledge quality instrument was examined for reliabilities, factor structure, and measurement model.
Satisfactory model fit of the knowledge quality framework allowed the research to further test the hypothesized relationship between knowledge quality and satisfaction and the subsequent influence of satisfaction on student’s attitudinal loyalty, and student’s learning outcomes. AMOS 20 was used to test the hypothesized relationships by employing the path analysis as a Structural Equation Modelling (SEM) technique.
Result of the path analysis supported all of the proposed relationships between the latent variables. It reveals that knowledge quality significantly influences students’ satisfaction from eLearning content. Subsequently, the students’ satisfaction significantly influences students’ learning outcomes (perceived academic performance, perceived learning effectiveness), and attitudinal loyalty.
The findings indicate that, to improve students’ learning outcomes and their loyalty towards the eLearning environment, it is important to maintain and improve the quality of knowledge gain. It will increase students’ satisfaction.
The framework would be useful to measure the knowledge quality of eLearning environment in terms of the knowledge gained by the user in an academic setting. An examination of the relationship between knowledge quality, satisfaction and subsequent eLearning academic and behavioural outcomes can suggest a better understanding for the improvement of eLearning environment
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