The Structure of the Retail and Service Industries of Jefferson County

The intent of this study is to review the current strengths and weaknesses of the retail and services industries of Jefferson County. We use historical data to look for overall trends and 2004 county sales tax data to provide detailed insights.

Robust query processing for linked data fragments

Linked Data Fragments (LDFs) refer to interfaces that allow for publishing and querying Knowledge Graphs on the Web. These interfaces primarily differ in their expressivity and allow for exploring different trade-offs when balancing the workload between clients and servers in decentralized SPARQL query processing. To devise efficient query plans, clients typically rely on heuristics that leverage the metadata provided by the LDF interface, since obtaining fine-grained statistics from remote sources is a challenging task. However, these heuristics are prone to potential estimation errors based on the metadata which can lead to inefficient query executions with a high number of requests, large amounts of data transferred, and, consequently, excessive execution times. In this work, we investigate robust query processing techniques for Linked Data Fragment clients to address these challenges. We first focus on robust plan selection by proposing CROP, a query plan optimizer that explores the cost and robustness of alternative query plans. Then, we address robust query execution by proposing a new class of adaptive operators: Polymorphic Join Operators. These operators adapt their join strategy in response to possible cardinality estimation errors. The results of our first experimental study show that CROP outperforms state-of-the-art clients by exploring alternative plans based on their cost and robustness. In our second experimental study, we investigate how different planning approaches can benefit from polymorphic join operators and find that they enable more efficient query execution in the majority of cases

The Relationship between Human Capital Efficiency and Financial Performance of Dutch Production Companies

Nowadays, Human Capital is recognized as the key factor in enhancing corporate performance of companies. However, very little is known about the efficiency of human capital in value creation for organizations and the key factors that can improve Human Capital Efficiency (HCE). This research aims to investigate the efficiency of Human Capital and its impact on the financial performance of Dutch production companies. Using data from 33 Dutch production companies for a period of 6 years (2007-2012) and applying the human capital component of the VAIC methodology the monetary value created by the companies’ knowledge workers is measured. Multiple linear regression models are used for analyzing the relationship between the performance of Human Capital and organizational performance measures including ROTA, ROE and EP. The study results revealed that there is positive relationship between HCE and all three corporate performance measures, amongst which it should be referred to the strongly statistically significant relationship between HCE and Employee Productivity (EP). This study contributes to the existing human capital theories by revealing the HCE of Dutch production companies and its impact on companies’ financial performance. Furthermore, it is significant in the sense that it will provide the companies’ managers with vital information required for making decisions on proper deployment of their human capital and investment in this strategic asset. Keywords: Human Capital Efficiency, Return on Total Asset, Return on Equity ,Employee Productivity, Value Added Intellectual Coefficient, Corporate Performance, Dutch production companie