Managing a portfolio of corporate venture units : challenges in achieving within-unit focus and between-unit coordination

Principal Topic: There is increasing recognition that the organizational configurations of corporate venture units should depend on the types of ventures the unit seeks to develop (Burgelman, 1984; Hill and Birkinshaw, 2008). Distinction have been made between internal and external as well as exploitative versus explorative ventures (Hill and Birkinshaw, 2008; Narayan et al., 2009; Schildt et al., 2005). Assuming that firms do not want to limit themselves to a single type of venture, but rather employ a portfolio of ventures, the logical consequence is that firms should employ multiple corporate venture units. Each venture unit tailor-made for the type of venture it seeks to develop. Surprisingly, there is limited attention in the literature for the challenges of managing multiple corporate venture units in a single firm. Maintaining multiple venture units within one firm provides easier access to funding for new ideas (Hamel, 1999). It allows for freedom and flexibility to tie the organizational systems (Rice et al., 2000), autonomy (Hill and Rothaermel, 2003), and involvement of management (Day, 1994; Wadwha and Kotha, 2006) to the requirements of the individual ventures. Yet, the strategic objectives of a venture may change when uncertainty around the venture is resolved (Burgelman, 1984). For example, firms may decide to spin-in external ventures (Chesbrough, 2002) or spun-out ventures that prove strategically unimportant (Burgelman, 1984). This suggests that ventures might need to be transferred between venture units, e.g. from a more internally-driven corporate venture division to a corporate venture capital unit. Several studies suggested that ventures require different managerial skills across their phase of development (Desouza et al., 2007; O'Connor and Ayers, 2005; Kazanjian and Drazin, 1990; Westerman et al., 2006). To facilitate effective transfer between venture units and manage the overall venturing process, it is important that firms set up and manage integrative linkages. Integrative linkages provide synergies and coordination between differentiated units (Lawrence and Lorsch, 1967). Prior findings pointed to the important role of senior management (Westerman et al., 2006; Gilbert, 2006) and a shared organizational vision (Burgers et al., 2009) to coordinate venture units with mainstream businesses. We will draw on these literatures to investigate the key question of how to integratively manage multiple venture units. ---------- Methodology/Key Propositions: In order to seek an answer to the research question, we employ a case study approach that provides unique insights into how firms can break up their venturing process. We selected three Fortune 500 companies that employ multiple venturing units, IBM, Royal Dutch/ Shell and Nokia, and investigated and compared their approaches. It was important that the case companies somewhat differed in the type of venture units they employed as well as the way they integrate and coordinate their venture units. The data are based on extensive interviews and a variety of internal and external company documents to triangulate our findings (Eisenhardt, 1989). The key proposition of the article is that firms can best manage their multiple venture units through an ambidextrous design of loosely coupled units. This provides venture units with sufficient flexibility to employ organizational configurations that best support the type of venture they seek to develop, as well as provides sufficient integration to facilitate smooth transfer of ventures between venture units. Based on the case findings, we develop a generic framework for a new way of managing the venturing process through multiple corporate venture units. ---------- Results and Implications: One of our main findings is that these firms tend to organize their venture units according to phases in the venture development process. That is, they tend to have venture units aimed at incubation of venture ideas as well as units aimed more at the commercialization of ventures into a new business unit for the firm or a start-up. The companies in our case studies tended to coordinate venture units through integrative management skills or a coordinative venture unit that spanned multiple phases. We believe this paper makes two significant contributions. First, we extend prior venturing literature by addressing how firms manage a portfolio of venture units, each achieving different strategic objectives. Second, our framework provides recommendations on how firms should manage such an approach towards venturing. This helps to increase the likelihood of success of their venturing programs.

Phenyl-ring disorder in the two-dimensional hydrogen-bonded structure of the 1:1 proton-transfer salt of the diazo-dye precursor 4-(phenyldiazenyl)aniline (aniline yellow) with L-tartaric acid

The structure of the 1:1 proton-transfer compound from the reaction of L-tartaric acid with the azo-dye precursor aniline yellow [4-(phenylazo)aniline], 4-(phenyldiazenyl)anilinium hydrogen 2R,3R-tartrate C12H12N3+ . C4H6O6- has been determined at 200 K. The asymmetric unit of the compound contains two independent phenylazoanilinium cations and two hydrogen L-tartrate anions. The structure is unusual in that all four phenyl rings of both cations have identical 50% rotational disorder. The two hydrogen L-tartrate anions form independent but similar chains through head-to-tail carboxylic O--H...O~carboxyl~ hydrogen bonds [graph set C7] which are then extended into a two-dimensional hydrogen-bonded sheet structure through hydroxyl O--H...O hydrogen-bonding links. The anilinium groups of the phenyldiazenyl cations are incorporated into the sheets and also provide internal hydrogen-bonding extensions while their aromatic tails layer in the structure without significant interaction except for weak \p--\p interactions [minimum ring centroid separation, 3.844(3) \%A]. The hydrogen L-tartrate residues of both anions have the common short intramolecular hydroxyl O--H...O~carboxyl~ hydogen bonds. This work has provided a solution to the unusual disorder problem inherent in the structure of this salt as well as giving another example of the utility of the hydrogen tartrate in the generation of sheet substructures in molecular assembly processes.

The problem child in Australian patent law : "fair" basing

The concept of "fair basing" is widely acknowledged as a difficult area of patent law. This article maps the development of fair basing law to demonstrate how some of the difficulties have arisen. Part I of the article traces the development of the branches of patent law that were swept under the nomenclature of "fair basing" by British legislation in 1949. It looks at the early courts' approach to patent construction, examines the early origin of fair basing and what it was intended to achiever. Part II of the article considers the modern interpretation of fair basing, which provides a striking contrast to its historical context. Without any consistent judicial approach to construction the doctrine has developed inappropriately, giving rise to both over-strict and over-generous approaches.

Does the fair basing "problem child" escape Lockwood?

In an earlier article the concept of fair basing in Australian patent law was described as a "problem child", often unruly and unpredictable in practice, but nevertheless understandable and useful in policy terms. The article traced the development of several different branches of patent law that were swept under the nomenclature of "fair basing" in Britain in 1949. It then went on to examine the adoption of fair basis into Australian law, the modern interpretation of the requirement, and its problems. This article provides an update. After briefly recapping on the relevant historical issues, it examines the recent Lockwood "internal" fair basing case in the Federal and High Courts.

A penalty-based genetic algorithm for the composite SaaS placement problem in the cloud

Cloud computing is a latest new computing paradigm where applications, data and IT services are provided over the Internet. Cloud computing has become a main medium for Software as a Service (SaaS) providers to host their SaaS as it can provide the scalability a SaaS requires. The challenges in the composite SaaS placement process rely on several factors including the large size of the Cloud network, SaaS competing resource requirements, SaaS interactions between its components and SaaS interactions with its data components. However, existing applications’ placement methods in data centres are not concerned with the placement of the component’s data. In addition, a Cloud network is much larger than data center networks that have been discussed in existing studies. This paper proposes a penalty-based genetic algorithm (GA) to the composite SaaS placement problem in the Cloud. We believe this is the first attempt to the SaaS placement with its data in Cloud provider’s servers. Experimental results demonstrate the feasibility and the scalability of the GA.

A hybrid genetic algorithm for the optimal constrained web service selection problem in web service composition

Web service composition is an important problem in web service based systems. It is about how to build a new value-added web service using existing web services. A web service may have many implementations, all of which have the same functionality, but may have different QoS values. Thus, a significant research problem in web service composition is how to select a web service implementation for each of the web services such that the composite web service gives the best overall performance. This is so-called optimal web service selection problem. There may be mutual constraints between some web service implementations. Sometimes when an implementation is selected for one web service, a particular implementation for another web service must be selected. This is so called dependency constraint. Sometimes when an implementation for one web service is selected, a set of implementations for another web service must be excluded in the web service composition. This is so called conflict constraint. Thus, the optimal web service selection is a typical constrained ombinatorial optimization problem from the computational point of view. This paper proposes a new hybrid genetic algorithm for the optimal web service selection problem. The hybrid genetic algorithm has been implemented and evaluated. The evaluation results have shown that the hybrid genetic algorithm outperforms other two existing genetic algorithms when the number of web services and the number of constraints are large.

Mobile robot navigation as a planar visual servoing problem

This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.

Mobile robot navigation as a planar visual servoing problem

This paper demonstrates some interesting connections between the hitherto disparate fields of mobile robot navigation and image-based visual servoing. A planar formulation of the well-known image-based visual servoing method leads to a bearing-only navigation system that requires no explicit localization and directly yields desired velocity. The well known benefits of image-based visual servoing such as robustness apply also to the planar case. Simulation results are presented.

The Validity of the Brief Michigan Alcohol Screening Test (bMAST) as a Problem Drinking Severity Measure

Objective: The Brief Michigan Alcoholism Screening Test (bMAST) is a 10-item test derived from the 25-item Michigan Alcoholism Screening Test (MAST). It is widely used in the assessment of alcohol dependence. In the absence of previous validation studies, the principal aim of this study was to assess the validity and reliability of the bMAST as a measure of the severity of problem drinking. Method: There were 6,594 patients (4,854 men, 1,740 women) who had been referred for alcohol-use disorders to a hospital alcohol and drug service who voluntarily participated in this study. Results: An exploratory factor analysis defined a two-factor solution, consisting of Perception of Current Drinking and Drinking Consequences factors. Structural equation modeling confirmed that the fit of a nine-item, two-factor model was superior to the original one-factor model. Concurrent validity was assessed through simultaneous administration of the Alcohol Use Disorders Identification Test (AUDIT) and associations with alcohol consumption and clinically assessed features of alcohol dependence. The two-factor bMAST model showed moderate correlations with the AUDIT. The two-factor bMAST and AUDIT were similarly associated with quantity of alcohol consumption and clinically assessed dependence severity features. No differences were observed between the existing weighted scoring system and the proposed simple scoring system. Conclusions: In this study, both the existing bMAST total score and the two-factor model identified were as effective as the AUDIT in assessing problem drinking severity. There are additional advantages of employing the two-factor bMAST in the assessment and treatment planning of patients seeking treatment for alcohol-use disorders. (J. Stud. Alcohol Drugs 68: 771-779,2007)

A hidden Markov model and relative entropy rate approach to vision-based dim target detection for UAV sense-and-avoid

Uninhabited aerial vehicles (UAVs) are a cutting-edge technology that is at the forefront of aviation/aerospace research and development worldwide. Many consider their current military and defence applications as just a token of their enormous potential. Unlocking and fully exploiting this potential will see UAVs in a multitude of civilian applications and routinely operating alongside piloted aircraft. The key to realising the full potential of UAVs lies in addressing a host of regulatory, public relation, and technological challenges never encountered be- fore. Aircraft collision avoidance is considered to be one of the most important issues to be addressed, given its safety critical nature. The collision avoidance problem can be roughly organised into three areas: 1) Sense; 2) Detect; and 3) Avoid. Sensing is concerned with obtaining accurate and reliable information about other aircraft in the air; detection involves identifying potential collision threats based on available information; avoidance deals with the formulation and execution of appropriate manoeuvres to maintain safe separation. This thesis tackles the detection aspect of collision avoidance, via the development of a target detection algorithm that is capable of real-time operation onboard a UAV platform. One of the key challenges of the detection problem is the need to provide early warning. This translates to detecting potential threats whilst they are still far away, when their presence is likely to be obscured and hidden by noise. Another important consideration is the choice of sensors to capture target information, which has implications for the design and practical implementation of the detection algorithm. The main contributions of the thesis are: 1) the proposal of a dim target detection algorithm combining image morphology and hidden Markov model (HMM) filtering approaches; 2) the novel use of relative entropy rate (RER) concepts for HMM filter design; 3) the characterisation of algorithm detection performance based on simulated data as well as real in-flight target image data; and 4) the demonstration of the proposed algorithm's capacity for real-time target detection. We also consider the extension of HMM filtering techniques and the application of RER concepts for target heading angle estimation. In this thesis we propose a computer-vision based detection solution, due to the commercial-off-the-shelf (COTS) availability of camera hardware and the hardware's relatively low cost, power, and size requirements. The proposed target detection algorithm adopts a two-stage processing paradigm that begins with an image enhancement pre-processing stage followed by a track-before-detect (TBD) temporal processing stage that has been shown to be effective in dim target detection. We compare the performance of two candidate morphological filters for the image pre-processing stage, and propose a multiple hidden Markov model (MHMM) filter for the TBD temporal processing stage. The role of the morphological pre-processing stage is to exploit the spatial features of potential collision threats, while the MHMM filter serves to exploit the temporal characteristics or dynamics. The problem of optimising our proposed MHMM filter has been examined in detail. Our investigation has produced a novel design process for the MHMM filter that exploits information theory and entropy related concepts. The filter design process is posed as a mini-max optimisation problem based on a joint RER cost criterion. We provide proof that this joint RER cost criterion provides a bound on the conditional mean estimate (CME) performance of our MHMM filter, and this in turn establishes a strong theoretical basis connecting our filter design process to filter performance. Through this connection we can intelligently compare and optimise candidate filter models at the design stage, rather than having to resort to time consuming Monte Carlo simulations to gauge the relative performance of candidate designs. Moreover, the underlying entropy concepts are not constrained to any particular model type. This suggests that the RER concepts established here may be generalised to provide a useful design criterion for multiple model filtering approaches outside the class of HMM filters. In this thesis we also evaluate the performance of our proposed target detection algorithm under realistic operation conditions, and give consideration to the practical deployment of the detection algorithm onboard a UAV platform. Two fixed-wing UAVs were engaged to recreate various collision-course scenarios to capture highly realistic vision (from an onboard camera perspective) of the moments leading up to a collision. Based on this collected data, our proposed detection approach was able to detect targets out to distances ranging from about 400m to 900m. These distances, (with some assumptions about closing speeds and aircraft trajectories) translate to an advanced warning ahead of impact that approaches the 12.5 second response time recommended for human pilots. Furthermore, readily available graphic processing unit (GPU) based hardware is exploited for its parallel computing capabilities to demonstrate the practical feasibility of the proposed target detection algorithm. A prototype hardware-in- the-loop system has been found to be capable of achieving data processing rates sufficient for real-time operation. There is also scope for further improvement in performance through code optimisations. Overall, our proposed image-based target detection algorithm offers UAVs a cost-effective real-time target detection capability that is a step forward in ad- dressing the collision avoidance issue that is currently one of the most significant obstacles preventing widespread civilian applications of uninhabited aircraft. We also highlight that the algorithm development process has led to the discovery of a powerful multiple HMM filtering approach and a novel RER-based multiple filter design process. The utility of our multiple HMM filtering approach and RER concepts, however, extend beyond the target detection problem. This is demonstrated by our application of HMM filters and RER concepts to a heading angle estimation problem.

A cooperative coevolutionary algorithm for the composite SaaS Placement Problem in the Cloud

Cloud computing has become a main medium for Software as a Service (SaaS) hosting as it can provide the scalability a SaaS requires. One of the challenges in hosting the SaaS is the placement process where the placement has to consider SaaS interactions between its components and SaaS interactions with its data components. A previous research has tackled this problem using a classical genetic algorithm (GA) approach. This paper proposes a cooperative coevolutionary algorithm (CCEA) approach. The CCEA has been implemented and evaluated and the result has shown that the CCEA has produced higher quality solutions compared to the GA.