Corporate governance development in privately held family businesses: a multiple case analysis

The objective of this study is to better understand and illustrate the process and the motivations for corporate governance implementation in Brazilian privately held family businesses. Three case companies were analyzed through an adapted developmental framework to illustrate the progression in corporate governance in response to changes in the ownership, investment and management dimensions over time. In this development, causal relationships between corporate governance and the three other framework dimensions were identified. It was found that the analyzed companies´ corporate governance implementation was motivated by the need to curb agency costs, whereas a cornerstone in this development was the first generational change. Only after the family businesses have reached the necessary maturity on all three dimensions, corporate governance practices were implemented. Put simply, the analyzed case companies developed formal systems as they grew more complex. This study complements the academic discussions on corporate governance in family businesses by offering Brazilian evidence on its underlying motivations and sequential implementation over time.

Applying supply chain management models in the banking industry: a brazilian case analysis

The study presents the results and recommendations deriving from the application of two supply chain management analysis models as proposed by the Supply Chain Council (SCOR, version 10.0) and by Lambert (1997, Framework for Supply Chain Management) on the logistics of cash transfers in Brazil. Cash transfers consist of the transportation of notes to and from each node of the complex network formed by the bank branches, ATMs, armored transportation providers, the government custodian, Brazilian Central Bank and financial institutions. Although the logistic to sustain these operations is so wide-ranged (country-size), complex and subject to a lot of financial regulations and security procedures, it has been detected that it was probably not fully integrated. Through the use of a primary and a secondary data research and analysis, using the above mentioned models, the study ends up with propositions to strongly improve the operations efficiency

A three-pronged approach to social business: a Brazilian multi-case analysis

Social businesses present a new paradigm to capitalism, in which private companies, non-profit organizations and civil society create a new type of business with the main objective of solving social problems with financial sustainability and efficiency through market mechanisms. As any new phenomenon, different authors conceptualize social businesses with distinct views. This article aims to present and characterize three different perspectives of social business definitions: the European, the American and that of the emerging countries. Each one of these views was illustrated by a different Brazilian case. We conclude with the idea that all the cases have similar characteristics, but also relevant differences that are more than merely geographical. The perspectives analyzed in this paper provide an analytical framework for understanding the field of social businesses. Moreover, the cases demonstrate that in the Brazilian context the field of social business is under construction and that as such it draws on different conceptual influences to deal with a complex and challenging reality.

Motivational interviewing and feedback for college drinkers: Handling missing values with complete case analysis and multiple imputation

Objective: In this secondary data analysis, three statistical methodologies were implemented to handle cases with missing data in a motivational interviewing and feedback study. The aim was to evaluate the impact that these methodologies have on the data analysis. ^ Methods: We first evaluated whether the assumption of missing completely at random held for this study. We then proceeded to conduct a secondary data analysis using a mixed linear model to handle missing data with three methodologies (a) complete case analysis, (b) multiple imputation with explicit model containing outcome variables, time, and the interaction of time and treatment, and (c) multiple imputation with explicit model containing outcome variables, time, the interaction of time and treatment, and additional covariates (e.g., age, gender, smoke, years in school, marital status, housing, race/ethnicity, and if participants play on athletic team). Several comparisons were conducted including the following ones: 1) the motivation interviewing with feedback group (MIF) vs. the assessment only group (AO), the motivation interviewing group (MIO) vs. AO, and the intervention of the feedback only group (FBO) vs. AO, 2) MIF vs. FBO, and 3) MIF vs. MIO.^ Results: We first evaluated the patterns of missingness in this study, which indicated that about 13% of participants showed monotone missing patterns, and about 3.5% showed non-monotone missing patterns. Then we evaluated the assumption of missing completely at random by Little's missing completely at random (MCAR) test, in which the Chi-Square test statistic was 167.8 with 125 degrees of freedom, and its associated p-value was p=0.006, which indicated that the data could not be assumed to be missing completely at random. After that, we compared if the three different strategies reached the same results. For the comparison between MIF and AO as well as the comparison between MIF and FBO, only the multiple imputation with additional covariates by uncongenial and congenial models reached different results. For the comparison between MIF and MIO, all the methodologies for handling missing values obtained different results. ^ Discussions: The study indicated that, first, missingness was crucial in this study. Second, to understand the assumptions of the model was important since we could not identify if the data were missing at random or missing not at random. Therefore, future researches should focus on exploring more sensitivity analyses under missing not at random assumption.^

Does immediate loading affect clinical and patient-centered outcomes of mandibular 2-unsplinted-implant overdenture? : a 2-year within-case analysis

Objective To provide 2-year clinical- and patient-oriented data with regard to mandibular overdenture assisted by 2 immediately loaded unsplinted implants. Material and methods In this pre-post design, Phase-I clinical trial, 18 edentate individuals (62.4 ± 7.7 years) received a new set of complete denture. Then, following standard procedures, 3 threaded implants (OsseoSpeed TX™, Dentsply Implants, Mölndal, Sweden) were placed in the mandible in each patient, and locator abutments (Zest Anchors LLC, Escondido, U.S.A.) were inserted on the right and left side implants. The midline implant served as a control for within-patient comparison. The immediate loading was conducted within 24 h of surgery. Data were collected at baseline (T0), 12 (T1) and 24 (T2) months after immediate loading. The clinical outcomes included implant survival rate, crestal bone level changes and implant stability. These criteria were assessed through clinical and radiographic examinations as well as resonance frequency analysis. Patient-centered outcomes included patient satisfaction and oral health-related quality of life measured using validated questionnaires. Brunner-Langer approach was used for statistical analysis. Results Implant survival rate for immediate loaded implants was 91.7% at 2-year follow-up. None of the unloaded implants failed. There was no statistically significant difference at baseline and follow-ups with regard to clinical outcomes between loaded and unloaded implants. Patient satisfaction and quality of life improved (p < 0.0001) from baseline to 2-year follow-up. Conclusion Immediate loading protocol did not negatively affect clinical outcomes, satisfaction and quality of life of patients wearing 2-unsplinted-implant mandibular overdenture for 2 years. This conclusion requires confirmation by randomized control trials. Clinical significance statement Mandibular overdenture assisted by two immediately-loaded unsplinted implants is successful treatment based on 2-year clinical and patient-based outcomes.

Does immediate loading affect clinical and patient-centered outcomes of mandibular 2-unsplinted-implant overdenture? : a 2-year within-case analysis

Objective To provide 2-year clinical- and patient-oriented data with regard to mandibular overdenture assisted by 2 immediately loaded unsplinted implants. Material and methods In this pre-post design, Phase-I clinical trial, 18 edentate individuals (62.4 ± 7.7 years) received a new set of complete denture. Then, following standard procedures, 3 threaded implants (OsseoSpeed TX™, Dentsply Implants, Mölndal, Sweden) were placed in the mandible in each patient, and locator abutments (Zest Anchors LLC, Escondido, U.S.A.) were inserted on the right and left side implants. The midline implant served as a control for within-patient comparison. The immediate loading was conducted within 24 h of surgery. Data were collected at baseline (T0), 12 (T1) and 24 (T2) months after immediate loading. The clinical outcomes included implant survival rate, crestal bone level changes and implant stability. These criteria were assessed through clinical and radiographic examinations as well as resonance frequency analysis. Patient-centered outcomes included patient satisfaction and oral health-related quality of life measured using validated questionnaires. Brunner-Langer approach was used for statistical analysis. Results Implant survival rate for immediate loaded implants was 91.7% at 2-year follow-up. None of the unloaded implants failed. There was no statistically significant difference at baseline and follow-ups with regard to clinical outcomes between loaded and unloaded implants. Patient satisfaction and quality of life improved (p < 0.0001) from baseline to 2-year follow-up. Conclusion Immediate loading protocol did not negatively affect clinical outcomes, satisfaction and quality of life of patients wearing 2-unsplinted-implant mandibular overdenture for 2 years. This conclusion requires confirmation by randomized control trials. Clinical significance statement Mandibular overdenture assisted by two immediately-loaded unsplinted implants is successful treatment based on 2-year clinical and patient-based outcomes.

IMPROVING THE PERFORMANCE OF DATABASE-CENTRIC APPLICATIONS THROUGH PROGRAM ANALYSIS

Modern software applications are becoming more dependent on database management systems (DBMSs). DBMSs are usually used as black boxes by software developers. For example, Object-Relational Mapping (ORM) is one of the most popular database abstraction approaches that developers use nowadays. Using ORM, objects in Object-Oriented languages are mapped to records in the database, and object manipulations are automatically translated to SQL queries. As a result of such conceptual abstraction, developers do not need deep knowledge of databases; however, all too often this abstraction leads to inefficient and incorrect database access code. Thus, this thesis proposes a series of approaches to improve the performance of database-centric software applications that are implemented using ORM. Our approaches focus on troubleshooting and detecting inefficient (i.e., performance problems) database accesses in the source code, and we rank the detected problems based on their severity. We first conduct an empirical study on the maintenance of ORM code in both open source and industrial applications. We find that ORM performance-related configurations are rarely tuned in practice, and there is a need for tools that can help improve/tune the performance of ORM-based applications. Thus, we propose approaches along two dimensions to help developers improve the performance of ORM-based applications: 1) helping developers write more performant ORM code; and 2) helping developers configure ORM configurations. To provide tooling support to developers, we first propose static analysis approaches to detect performance anti-patterns in the source code. We automatically rank the detected anti-pattern instances according to their performance impacts. Our study finds that by resolving the detected anti-patterns, the application performance can be improved by 34% on average. We then discuss our experience and lessons learned when integrating our anti-pattern detection tool into industrial practice. We hope our experience can help improve the industrial adoption of future research tools. However, as static analysis approaches are prone to false positives and lack runtime information, we also propose dynamic analysis approaches to further help developers improve the performance of their database access code. We propose automated approaches to detect redundant data access anti-patterns in the database access code, and our study finds that resolving such redundant data access anti-patterns can improve application performance by an average of 17%. Finally, we propose an automated approach to tune performance-related ORM configurations using both static and dynamic analysis. Our study shows that our approach can help improve application throughput by 27--138%. Through our case studies on real-world applications, we show that all of our proposed approaches can provide valuable support to developers and help improve application performance significantly.

Improving the Performance of Database-Centric Applications Through Program Analysis

Thesis (Ph.D, Computing) -- Queen's University, 2016-09-30 09:55:51.506

Performance characteristic of moving average trading rules in the Finnish stock market

The thesis examines the profitability of DMAC trading rules in the Finnish stock market over the 1996-2012 period. It contributes to the existing technical analysis literature by comparing for the first time the performance of DMAC strategies based on individual stock trading portfolios to the performance of index trading strategies based on the trading on the index (OMX Helsinki 25) that consists of the same stocks. Besides, the market frictions including transaction costs and taxes are taken into account, and the results are reported from both institutional and individual investor’s perspective. Performance characteristic of DMAC rules are evaluated by simulating 19,900 different trading strategies in total for two non- overlapping 8-year sub-periods, and decomposing the full-sample-period performance of DMAC trading strategies into distinct bullish- and bearish-period performances. The results show that the best DMAC rules have predictive power on future price trends, and these rules are able to outperform buy-and-hold strategy. Although the performance of the DMAC strategies is highly dependent on the combination of moving average lengths, the best DMAC rules of the first sub-period have also performed well during the latter sub-period in the case of individual stock trading strategies. According to the results, the outperformance of DMAC trading rules over buy-and-hold strategy is mostly attributed to their superiority during the bearish periods, and particularly, during stock market crashes.

What makes online grocers work? A case study analysis of factors contributing to online grocery store profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. ^ To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. ^ Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. ^ The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance. ^

What Makes Online Grocers Work? A Case Study Analysis of Factors Contributing to Online Grocery Store Profitability

This research examined the factors contributing to the performance of online grocers prior to, and following, the 2000 dot.com collapse. The primary goals were to assess the relationship between a company’s business model(s) and its performance in the online grocery channel and to determine if there were other company and/or market related factors that could account for company performance. To assess the primary goals, a case based theory building process was utilized. A three-way cross-case analysis comprising Peapod, GroceryWorks, and Tesco examined the common profit components, the structural category (e.g., pure-play, partnership, and hybrid) profit components, and the idiosyncratic profit components related to each specific company. Based on the analysis, it was determined that online grocery store business models could be represented at three distinct, but hierarchically, related levels. The first level was termed the core model and represented the basic profit structure that all online grocers needed in order to conduct operations. The next model level was termed the structural model and represented the profit structure associated with the specific business model configuration (i.e., pure-play, partnership, hybrid). The last model level was termed the augmented model and represented the company’s business model when idiosyncratic profit components were included. In relation to the five company related factors, scalability, rate of expansion, and the automation level were potential candidates for helping to explain online grocer performance. In addition, all the market structure related factors were deemed possible candidates for helping to explain online grocer performance. The study concluded by positing an alternative hypothesis concerning the performance of online grocers. Prior to this study, the prevailing wisdom was that the business models were the primary cause of online grocer performance. However, based on the core model analysis, it was hypothesized that the customer relationship activities (i.e., advertising, promotions, and loyalty program tie-ins) were the real drivers of online grocer performance.