Ownership versus Management Effects on Performance in Family and Founder Companies: A Bayesian Analysis

There are ongoing debates in the literature concerning the performance of family firms: some studies find superior performance among these companies, others find negative or neutral per-formance effects. In this research we employ agency theory to argue that the effects of family ownership vs. family management will be quite different: the former is expected to contribute positively to performance, the latter is argued to erode performance. Previous studies, due to problems of omitted variables or multicollinearity have been unable to distinguish these effects. Using a Bayesian approach that avoids these problems, we find that whereas family and founder ownership are associated with superior performance, the results for family management and even founder management are far more ambiguous. Our results have implications regarding the own-ership and management of lone founder and family firms.Family firms; lone founder firms; performance; Bayesian analysis; agency theory

Concepts to Interfere with Protein-Protein Complex Formations: Data Analysis, Structural Evidence and Strategies for Finding Small Molecule Modulators

(1) Analyzing protein-protein interactions at the atomic level is critical for our understanding of the principles governing the interactions involved in protein-protein recognition. For this purpose descriptors explaining the nature of different protein-protein complexes are desirable. In this work, we introduce Epic Protein Interface Classification (EPIC) as a framework handling the preparation, processing, and analysis of protein-protein complexes for classification with machine learning algorithms. We applied four different machine learning algorithms: Support Vector Machines (SVM), C4.5 Decision Trees, K Nearest Neighbors (KNN), and Naïve Bayes (NB) algorithm in combination with three feature selection methods, Filter (Relief F), Wrapper, and Genetic Algorithms (GA) to extract discriminating features from the protein-protein complexes. To compare protein-protein complexes to each other, we represented the physicochemical characteristics of their interfaces in four different ways, using two different atomic contact vectors (ACVs), DrugScore pair potential vectors (DPV) and SFCscore descriptor vectors (SDV). We classified two different datasets: (A) 172 protein-protein complexes comprising 96 monomers, forming contacts enforced by the crystallographic packing environment (crystal contacts), and 76 biologically functional homodimer complexes; (B) 345 protein-protein complexes containing 147 permanent complexes and 198 transient complexes. We were able to classify up to 94.8% of the packing enforced/functional and up to 93.6% of the permanent/transient complexes correctly. Furthermore, we were able to extract relevant features from the different protein-protein complexes and introduce an approach for scoring the importance of the extracted features. (2) Since protein-protein interactions play pivotal role in the communication on the molecular level in virtually every biological system and process, the search and design for modulators of such interactions is of utmost interest. In recent years many inhibitors for specific protein-protein interactions have been developed, however, in only a few cases, small and druglike molecules are able to interfere the complex formation of proteins. On the other hand, there a several small molecules known to modulate protein-protein interactions by means of stabilizing an already assembled complex. To achieve this goal, a ligand is binding to a pocket, which is located rim-exposed at the interface of the interacting proteins, e.g. as the phytotoxin Fusicoccin, which stabilizes the interaction of plant H+-ATPase and 14-3-3 protein by nearly a factor of 100. To suggest alternative leads, we performed a virtual screening campaign to discover new molecules putatively stabilizing this complex. Furthermore, we screen a dataset of 198 transient recognition protein-protein complexes for cavities, which are located rim-exposed at their interfaces. We provide evidence for high similarity between such rim-exposed cavities and usual ligand accommodating active sites of enzymes. This analysis suggests that rim-exposed cavities at protein-protein interfaces are druggable targets. Therefore, the principle of stabilizing protein-protein interactions seems to be a promising alternative to the approach of the competitive inhibition of such interactions by small molecules. (3) AffinDB is a database of affinity data for structurally resolved protein-ligand complexes from the PDB. It is freely accessible at http://www.agklebe.de/affinity. Affinity data are collected from the scientific literature, both from primary sources describing the original experimental work of affinity determination and from secondary references which report affinity values determined by others. AffinDB currently contains over 730 affinity entries covering more than 450 different protein-ligand complexes. Besides the affinity value, PDB summary information and additional data are provided, including the experimental conditions of the affinity measurement (if available in the corresponding reference); 2D drawing, SMILES code, and molecular weight of the ligand; links to other databases, and bibliographic information. AffinDB can be queried by PDB code or by any combination of affinity range, temperature and pH-value of the measurement, ligand molecular weight, and publication data (author, journal, year). Search results can be saved as tabular reports in text files. The database is supposed to be a valuable resource for researchers interested in biomolecular recognition and the development of tools for correlating structural data with affinities, as needed, for example, in structure-based drug design

Direct Air Capture (DAC) in Germany : resource implications of a possible rollout in 2045

Direct Air Capture (DAC) is increasingly being discussed as a possibility to limit climate change. In this study, a possible rollout of the DAC technology at German coastal areas is analysed based on an existing climate neutrality scenario. For the year 2045 the resulting costs as well as land, water and energy consumption are examined. It is concluded that a realization of the DAC technology in Germany might be possible from a technical point of view. However, there is a high demand for land and energy. Since a rollout is needed to start in 20 years at the latest, the required discussion and evaluation should be initiated as quickly as possible

Beyond survival? People management strategies for development and growth of PSBs in a fragmented digital media landscape

Overview It is a universal truth that media companies rely on the talent and creativity of their staff more than almost any other industrial sector. Therefore effective human resource management(HRM) is a vital tool to enable company success. A number of studies have considered this matter for the Public Service Broadcasters(PSBs) in this ever-changing ecosystem. Most have taken a sectorial approach, a top down review. This research examines HRM from the bottom up. It reviewed the matter of people management that differentiates the media sector from others and the capabilities that give the individual organisation a competitive advantage over others within the sector. The study This summary reports on a pilot study conducted by the University of Westminster in partnership with the Public Media Alliance(PMA) in the first quarter of 2019. The research was designed to contribute to our understanding of HRM processes within PSBs. Specifically, the research examined the processes by which the PSB manages the employee – employer relationship over the employment lifecycle. The implicit research question considers whether public service media(PSM) organisations have a coherent, strategic approach to HRM. The fieldwork The importance of this pilot study is predicated on the argument that a diverse and inclusive workforce is key to success in all sectors of the creative industries. The scope of work was to conduct a review of human resource management (HRM) processes within PSBs drawn from a cross-section of PMA members. The study benchmarked a sample group against a comparator set using a qualitative self-evaluation tool based on a HRM maturity model. This is an assessment tool that helps the HR professional to identify the weaknesses of internal HRM Systems, by comparing the maturity map of their company with the standard HRM maturity map. The model applied in this study defines 22 HRM attributes to create a performance index of people management. These attributes are clustered under Diversity & Inclusion (D&I) and Learning & Development (L&D) that cover strategy, action and evaluation, as shown in the presentation accompanying this summary. The HRM maturity model Archetypal HRM performances can be described as Poor - reactive with an Index score of up to 33%, Average - transactional with an Index score between 33 - 66%, or High - strategic leadership with an Index score above 66%. Findings Overall a picture emerges of HRM processes being transactional in nature within the pilot study PSBs. There is an absence of vision and strategic thinking. The lowest index score was 16% and highest 86%. These scores were cross-referenced with the publicly available documents produced by the broadcasters from which it is concluded that the ’16’ was brutally honest and the ’86’ an overstatement. The research revealed a number of anodyne statements supporting HRM but with limited over-arching ambition, commitment and statement of purpose. There were few publicly stated policies and limited publicly available evidence of HRM targets. Three organisations were used as benchmark comparators; two broadcasters - the BBC and Channel 4 (UK) plus Ernst & Young (EY) a global leader in HRM processes with a wealth of public documents on best practice. It was clear from the external audit of the pilot PSBs that PMA organizations that follow the BBC or the Channel 4 HRM governance model as template go beyond compliance. Those that don’t follow the BBC model produce annual reports with very limited focus on employees. There is a focus by Asian PSM organisations to present their leaders not leadership. Triangulating the scores with the supporting documentation it was evident that there was some overstatement of HRM actions. This was not helped by the lack of transparency by most PSBs in the pilot study. Implications Existing research overwhelmingly concludes that well managed HRM is good for business. Some PMA companies in the pilot group appear to be under-performing in HRM versus their competitive set and comparators. This has implications for risk management with non-compliance to legal frameworks; lost opportunities for talent recruitment and retention; and corporate values and reputation with the wider stakeholder community. If nothing else, good people management is the right thing to do. Recommendations and next steps The indications are that PSMs organisations lag the competition; current approaches represent an organisational risk. However, this study revealed that there are examples of good practice across the sector, but they do need to be shared. The full report provides a set of recommendations under three stages to high performance. These stages suggest that PSBs take some immediate practical steps to improve HRM performance. Some PSBs need to define a strategy and associated processes for execution. The PMA should create a HRM community. Collectively that community should build on the exemplars to share good practice. It is recommended that the PMA conducts a full study to gather examples of good practice to share within a community of practice. As noted elsewhere by the PMA, collaboration is key to the survival of PSM

Concepts to Interfere with Protein-Protein Complex Formations: Data Analysis, Structural Evidence and Strategies for Finding Small Molecule Modulators

(1) Analyzing protein-protein interactions at the atomic level is critical for our understanding of the principles governing the interactions involved in protein-protein recognition. For this purpose descriptors explaining the nature of different protein-protein complexes are desirable. In this work, we introduce Epic Protein Interface Classification (EPIC) as a framework handling the preparation, processing, and analysis of protein-protein complexes for classification with machine learning algorithms. We applied four different machine learning algorithms: Support Vector Machines (SVM), C4.5 Decision Trees, K Nearest Neighbors (KNN), and Naïve Bayes (NB) algorithm in combination with three feature selection methods, Filter (Relief F), Wrapper, and Genetic Algorithms (GA) to extract discriminating features from the protein-protein complexes. To compare protein-protein complexes to each other, we represented the physicochemical characteristics of their interfaces in four different ways, using two different atomic contact vectors (ACVs), DrugScore pair potential vectors (DPV) and SFCscore descriptor vectors (SDV). We classified two different datasets: (A) 172 protein-protein complexes comprising 96 monomers, forming contacts enforced by the crystallographic packing environment (crystal contacts), and 76 biologically functional homodimer complexes; (B) 345 protein-protein complexes containing 147 permanent complexes and 198 transient complexes. We were able to classify up to 94.8% of the packing enforced/functional and up to 93.6% of the permanent/transient complexes correctly. Furthermore, we were able to extract relevant features from the different protein-protein complexes and introduce an approach for scoring the importance of the extracted features. (2) Since protein-protein interactions play pivotal role in the communication on the molecular level in virtually every biological system and process, the search and design for modulators of such interactions is of utmost interest. In recent years many inhibitors for specific protein-protein interactions have been developed, however, in only a few cases, small and druglike molecules are able to interfere the complex formation of proteins. On the other hand, there a several small molecules known to modulate protein-protein interactions by means of stabilizing an already assembled complex. To achieve this goal, a ligand is binding to a pocket, which is located rim-exposed at the interface of the interacting proteins, e.g. as the phytotoxin Fusicoccin, which stabilizes the interaction of plant H+-ATPase and 14-3-3 protein by nearly a factor of 100. To suggest alternative leads, we performed a virtual screening campaign to discover new molecules putatively stabilizing this complex. Furthermore, we screen a dataset of 198 transient recognition protein-protein complexes for cavities, which are located rim-exposed at their interfaces. We provide evidence for high similarity between such rim-exposed cavities and usual ligand accommodating active sites of enzymes. This analysis suggests that rim-exposed cavities at protein-protein interfaces are druggable targets. Therefore, the principle of stabilizing protein-protein interactions seems to be a promising alternative to the approach of the competitive inhibition of such interactions by small molecules. (3) AffinDB is a database of affinity data for structurally resolved protein-ligand complexes from the PDB. It is freely accessible at http://www.agklebe.de/affinity. Affinity data are collected from the scientific literature, both from primary sources describing the original experimental work of affinity determination and from secondary references which report affinity values determined by others. AffinDB currently contains over 730 affinity entries covering more than 450 different protein-ligand complexes. Besides the affinity value, PDB summary information and additional data are provided, including the experimental conditions of the affinity measurement (if available in the corresponding reference); 2D drawing, SMILES code, and molecular weight of the ligand; links to other databases, and bibliographic information. AffinDB can be queried by PDB code or by any combination of affinity range, temperature and pH-value of the measurement, ligand molecular weight, and publication data (author, journal, year). Search results can be saved as tabular reports in text files. The database is supposed to be a valuable resource for researchers interested in biomolecular recognition and the development of tools for correlating structural data with affinities, as needed, for example, in structure-based drug design