Dynamic capabilities and strategic paradox: a case study

Today’s business leaders must constantly review and develop their firm’s abilities to adapt to and benefit from external changes. Dynamic capabilities are the capacity of an organization to purposefully create, extend or modify its resource base. They enable it to exploit business, technological and market opportunities and adapt to market changes, an ability more often observed in highly dynamic industries, such as consumer electronics or telecommunications. Using the case study method, this article identifies dynamic capabilities in traditional, less dynamic industries when faced with a sudden drop of revenue. Four distinct routines emerge, namely structure and practices enduring time-sensitive strategic decision-making by the tice, and a culture encouraging learning and coevolving. Seemingly strategic paradox objectives encourage the management team to question the status quo and, when managed well, transform the tensions between old and new into an ability to advance superior ideas faster.

Resource-based view and dynamic capabilities - Achieving competitive advantage through internal resources and competences

Strategy has always been important for success. Whether strategy is applied for military purposes, in large firms, or even for personal objectives, there are certain key characteristics that every successful strategy carries on: clear, objective and simple goals; deep knowledge and understanding of the competitive environment; objective understanding and exploitation of resources; and an effective plan implementation. In this paper, the author’s attention will be focused on the role of internal resources, routines and processes as the bases of sustained competitive advantage (hereafter SCA) into what is now known as the resourcebased view of the firm (RBV) and Dynamic Capabilities (DC). First, the relevance of RBV and DC approaches and the main characteristics of those are briefly mentioned. Second, RBV and DC are examined as an important piece to achieve SCA. Later on, the author deepens into some examples and the manager’s importance when using these RBV and DC approaches. Then issues related with complexity and undefined concepts in RBV and DC are briefly mentioned. Finally, conclusions and personal comments are presented.

Closing the productivity gap and trade *policy

The relationship between trade policy and productivity growth is regarded as ambiguous in the literature. This dissertation examines under what condition the relationship would be positive (or negative). Through the use of static and dynamic analysis, we find two conflicting effects (the pro-protection effect and the pro-competitive effect) that cause the relationship to be ambiguous. If there exists a productivity gap between the import-competing and foreign industries, and if the level of protection is low (high), the relationship is positive (negative). We also show that the import-competing firm responds to a change in the protection level by choosing a level of investment in innovation which yields a different rate of productivity growth. The policy implication, therefore, is that a trade-policy maker should set the trade protection at a level which induces the firm to choose the highest rate of productivity growth, and, as a result, leading the firm to close the initial productivity gap in the most efficient way. ^

Design of a dynamic e-commerce system with engineering applications

The primary purpose of this thesis was to design and develop a prototype e-commerce system where dynamic parameters are included in the decision-making process and execution of an online transaction. The system developed and implemented takes into account previous usage history, priority and associated engineering capabilities. The system was developed using three-tiered client server architecture. The interface was the Internet browser. The middle tiered web server was implemented using Active Server Pages, which form a link between the client system and other servers. A relational database management system formed the data component of the three-tiered architecture. It includes a capability for data warehousing which extracts needed information from the stored data of the customers as well as their orders. The system organizes and analyzes the data that is generated during a transaction to formulate a client's behavior model during and after a transaction. This is used for making decisions like pricing, order rescheduling during a client's forthcoming transaction. The system helps among other things to bring about predictability to a transaction execution process, which could be highly desirable in the current competitive scenario.

Essays in Industrial Organization

This dissertation extends the empirical industrial organization literature with two essays on strategic decisions of firms in imperfectly competitive markets and one essay on how inertia in consumer choice can result in significant welfare losses. Using data from the airline industry I study a well-known puzzle in the literature whereby incumbent firms decrease fares when Southwest Airlines emerges as a potential entrant, but is not (yet) competing directly. In the first essay I describe this so-called Southwest Effect and use reduced-form analysis to offer possible explanations for why firms may choose to forgo profits today rather than wait until Southwest operates the route. The analysis suggests that incumbent firms are attempting to signal to Southwest that entry is unprofitable so as to deter its entry. The second essay develops this theme by extending a classic model from the IO literature, limit pricing, to a dynamic setting. Calibrations indicate the price cuts observed in the data can be captured by a dynamic limit pricing model. The third essay looks at another concentrated industry, mobile telecoms, and studies how inertia in choice (be it inattention or switching costs) can lead to consumers being on poorly matched cellphone plans and how a simple policy proposal can have a considerable effect on welfare.

Dynamic Life Cycle Assessment Modeling Approaches for Transboundary Energy Feedstocks

The rise of the twenty-first century has seen the further increase in the industrialization of Earth’s resources, as society aims to meet the needs of a growing population while still protecting our environmental and natural resources. The advent of the industrial bioeconomy – which encompasses the production of renewable biological resources and their conversion into food, feed, and bio-based products – is seen as an important step in transition towards sustainable development and away from fossil fuels. One sector of the industrial bioeconomy which is rapidly being expanded is the use of biobased feedstocks in electricity production as an alternative to coal, especially in the European Union.

As bioeconomy policies and objectives increasingly appear on political agendas, there is a growing need to quantify the impacts of transitioning from fossil fuel-based feedstocks to renewable biological feedstocks. Specifically, there is a growing need to conduct a systems analysis and potential risks of increasing the industrial bioeconomy, given that the flows within it are inextricably linked. Furthermore, greater analysis is needed into the consequences of shifting from fossil fuels to renewable feedstocks, in part through the use of life cycle assessment modeling to analyze impacts along the entire value chain.

To assess the emerging nature of the industrial bioeconomy, three objectives are addressed: (1) quantify the global industrial bioeconomy, linking the use of primary resources with the ultimate end product; (2) quantify the impacts of the expaning wood pellet energy export market of the Southeastern United States; (3) conduct a comparative life cycle assessment, incorporating the use of dynamic life cycle assessment, of replacing coal-fired electricity generation in the United Kingdom with wood pellets that are produced in the Southeastern United States.

To quantify the emergent industrial bioeconomy, an empirical analysis was undertaken. Existing databases from multiple domestic and international agencies was aggregated and analyzed in Microsoft Excel to produce a harmonized dataset of the bioeconomy. First-person interviews, existing academic literature, and industry reports were then utilized to delineate the various intermediate and end use flows within the bioeconomy. The results indicate that within a decade, the industrial use of agriculture has risen ten percent, given increases in the production of bioenergy and bioproducts. The underlying resources supporting the emergent bioeconomy (i.e., land, water, and fertilizer use) were also quantified and included in the database.

Following the quantification of the existing bioeconomy, an in-depth analysis of the bioenergy sector was conducted. Specifically, the focus was on quantifying the impacts of the emergent wood pellet export sector that has rapidly developed in recent years in the Southeastern United States. A cradle-to-gate life cycle assessment was conducted in order to quantify supply chain impacts from two wood pellet production scenarios: roundwood and sawmill residues. For reach of the nine impact categories assessed, wood pellet production from sawmill residues resulted in higher values, ranging from 10-31% higher.

The analysis of the wood pellet sector was then expanded to include the full life cycle (i.e., cradle-to-grave). In doing to, the combustion of biogenic carbon and the subsequent timing of emissions were assessed by incorporating dynamic life cycle assessment modeling. Assuming immediate carbon neutrality of the biomass, the results indicated an 86% reduction in global warming potential when utilizing wood pellets as compared to coal for electricity production in the United Kingdom. When incorporating the timing of emissions, wood pellets equated to a 75% or 96% reduction in carbon dioxide emissions, depending upon whether the forestry feedstock was considered to be harvested or planted in year one, respectively.

Finally, a policy analysis of renewable energy in the United States was conducted. Existing coal-fired power plants in the Southeastern United States were assessed in terms of incorporating the co-firing of wood pellets. Co-firing wood pellets with coal in existing Southeastern United States power stations would result in a nine percent reduction in global warming potential.

Estimating Dynamic Treatment Effects from Project STAR (Working Paper 36)

This paper considers the analysis of data from randomized trials which offer a sequence of interventions and suffer from a variety of problems in implementation. In experiments that provide treatment in multiple periods (T>1), subjects have up to 2^{T}-1 counterfactual outcomes to be estimated to determine the full sequence of causal effects from the study. Traditional program evaluation and non-experimental estimators are unable to recover parameters of interest to policy makers in this setting, particularly if there is non-ignorable attrition. We examine these issues in the context of Tennessee's highly influential randomized class size study, Project STAR. We demonstrate how a researcher can estimate the full sequence of dynamic treatment effects using a sequential difference in difference strategy that accounts for attrition due to observables using inverse probability weighting M-estimators. These estimates allow us to recover the structural parameters of the small class effects in the underlying education production function and construct dynamic average treatment effects. We present a complete and different picture of the effectiveness of reduced class size and find that accounting for both attrition due to observables and selection due to unobservable is crucial and necessary with data from Project STAR

Development of DYNAMIX Policy Mixes - Deliverable 4.2, revised version, of the DYNAMIX project

This report documents the development of the initial dynamic policy mixes that were developed for assessment in the DYNAMIX project. The policy mixes were designed within three different policy areas: overarching policy, land-use and food, and metals and other materials. The policy areas were selected to address absolute decoupling in general and, specifically, the DYNAMIX targets related to the use of virgin metals, the use of arable land and freshwater, the input of the nutrients nitrogen and phosphorus, and emissions of greenhouse gases. Each policy mix was developed within a separate author team, using a common methodological framework that utilize previous findings in the project. Specific drivers and barriers for resource use and resource efficiency are discussed in each policy area. Specific policy objectives and targets are also discussed before the actual policy mix is presented. Each policy mix includes a set of key instruments, which can be embedded in a wider set of supporting and complementary policy instruments. All key instruments are described in the report through responses to a set of predefined questions. The overarching mix includes a broad variety of key instruments. The land-use policy mix emphasizes five instruments to improve food production through, for example, revisions of already existing policy documents. It also includes three instruments to influence the food consumption and food waste. The policy mix on metals and other materials primarily aims at reducing the use of virgin metals through increased recycling, increased material efficiency and environmentally justified material substitution. To avoid simply shifting of burdens, it includes several instruments of an overarching character.

Policy mixes for resource efficiency – conceptual issues, design and assessment challenges

Since the 1950s the global consumption of natural resources has skyrocketed, both in magnitude and in the range of resources used. Closely coupled with emissions of greenhouse gases, land consumption, pollution of environmental media, and degradation of ecosystems, as well as with economic development, increasing resource use is a key issue to be addressed in order to keep the planet Earth in a safe and just operating space. This requires thinking about absolute reductions in resource use and associated environmental impacts, and, when put in the context of current re-focusing on economic growth at the European level, absolute decoupling, i.e., maintaining economic development while absolutely reducing resource use and associated environmental impacts. Changing behavioural, institutional and organisational structures that lock-in unsustainable resource use is, thus, a formidable challenge as existing world views, social practices, infrastructures, as well as power structures, make initiating change difficult. Hence, policy mixes are needed that will target different drivers in a systematic way. When designing policy mixes for decoupling, the effect of individual instruments on other drivers and on other instruments in a mix should be considered and potential negative effects be mitigated. This requires smart and time-dynamic policy packaging. This Special Issue investigates the following research questions: What is decoupling and how does it relate to resource efficiency and environmental policy? How can we develop and realize policy mixes for decoupling economic development from resource use and associated environmental impacts? And how can we do this in a systemic way, so that all relevant dimensions and linkages—including across economic and social issues, such as production, consumption, transport, growth and wellbeing­—are taken into account? In addressing these questions, the overarching goals of this Special Issue are to: address the challenges related to more sustainable resource-use; contribute to the development of successful policy tools and practices for sustainable development and resource efficiency (particularly through the exploration of socio-economic, scientific, and integrated aspects of sustainable development); and inform policy debates and policy-making. The Special Issue draws on findings from the EU and other countries to offer lessons of international relevance for policy mixes for more sustainable resource-use, with findings of interest to policy makers in central and local government and NGOs, decision makers in business, academics, researchers, and scientists.

Between Principle and Practicality: A Dynamic Realist Examination of Independence in the Canadian Justice System

This work examines independence in the Canadian justice system using an approach adapted from new legal realist scholarship called ‘dynamic realism’. This approach proposes that issues in law must be considered in relation to their recursive and simultaneous development with historic, social and political events. Such events describe ‘law in action’ and more holistically demonstrate principles like independence, rule of law and access to justice. My dynamic realist analysis of independence in the justice system employs a range methodological tools and approaches from the social sciences, including: historical and historiographical study; public administrative; policy and institutional analysis; an empirical component; as well as constitutional, statutory interpretation and jurisprudential analysis. In my view, principles like independence represent aspirational ideals in law which can be better understood by examining how they manifest in legal culture and in the legal system. This examination focuses on the principle and practice of independence for both lawyers and judges in the justice system, but highlights the independence of the Bar. It considers the inter-relation between lawyer independence and the ongoing refinement of judicial independence in Canadian law. It also considers both independence of the Bar and the Judiciary in the context of the administration of justice, and practically illustrates the interaction between these principles through a case study of a specific aspect of the court system. This work also focuses on recent developments in the principle of Bar independence and its relation to an emerging school of professionalism scholarship in Canada. The work concludes by describing the principle of independence as both conditional and dynamic, but rooted in a unitary concept for both lawyers and judges. In short, independence can be defined as impartiality, neutrality and autonomy of legal decision-makers in the justice system to apply, protect and improve the law for what has become its primary normative purpose: facilitating access to justice. While both independence of the Bar and the Judiciary are required to support access to independent courts, some recent developments suggest the practical interactions between independence and access need to be the subject of further research, to better account for both the principles and the practicalities of the Canadian justice system.

El multilateralismo como intervencionismo. Estados Unidos y la Sociedad de Naciones en América Latina (1930-1946)

Este artículo analiza una dinámica de intervenciones de Estados Unidos en América Latina que no ha atraído suficientemente la atención de los historiadores. En los años treinta y cuarenta, cuando Europa se hundía en una nueva confrontación bélica, ciertos sectores del gobierno y del mundo empresarial norteamericano intentaron articular una nueva relación con los países del continente basada en una propuesta de multilateralismo que se había configurado dentro de la Sociedad de Naciones (SN). Estos estadounidenses intentaron establecer una dinámica de relaciones triangulares con los gobiernos latinoamericanos y los organismos técnicos de la SN. Gracias a ello, como se mostrará en este artículo para el caso del funcionamiento del Comité Fiscal de la Sociedad de Naciones, los latinoamericanos fueron capaces de influir en el tipo de políticas que debían emanar de esta relación triangular. La importancia de esta historia no es menor. La relación triangular entre Estados Unidos, América Latina y la SN sirvió de base para la reconstrucción de la gobernanza global liderada por los Estados Unidos tras la guerra.

Value creation in a reregulated market : Divestments, firms and dynamic processes

This thesis makes use of the unique reregulation of pharmaceutical monopoly in Sweden to critically examine intraindustry firm heterogeneity. It contributes to existing divestiture research as it studies the dynamism in between reconfigurations of value constellations and its effects on value creation of divested pharmacies. Because the findings showed that the predominant theory of intraindustry firm heterogeneity could not explain firm performance, the value constellation concept was applied as it captured the phenomena. A patterned finding informed how reconfigurations of value constellations in a reregulated market characterized by strict rules, regulations, and high competition did not generate additional value for firms on short term. My study unveils that value creation is hampered in situations where rules and regulations significantly affect firms’ ability to reconfigure their value constellations. The key practical implication is an alternative perspective on fundamental aspects of the reregulation and how policy-makers may impede firm performance and the intended creation of new value for not only firms but for society as a whole.

A generic strategy for dynamic load balancing of distributed memory parallel computational mechanics using unstructured meshes

A large class of computational problems are characterised by frequent synchronisation, and computational requirements which change as a function of time. When such a problem is solved on a message passing multiprocessor machine [5], the combination of these characteristics leads to system performance which deteriorate in time. As the communication performance of parallel hardware steadily improves so load balance becomes a dominant factor in obtaining high parallel efficiency. Performance can be improved with periodic redistribution of computational load; however, redistribution can sometimes be very costly. We study the issue of deciding when to invoke a global load re-balancing mechanism. Such a decision policy must actively weigh the costs of remapping against the performance benefits, and should be general enough to apply automatically to a wide range of computations. This paper discusses a generic strategy for Dynamic Load Balancing (DLB) in unstructured mesh computational mechanics applications. The strategy is intended to handle varying levels of load changes throughout the run. The major issues involved in a generic dynamic load balancing scheme will be investigated together with techniques to automate the implementation of a dynamic load balancing mechanism within the Computer Aided Parallelisation Tools (CAPTools) environment, which is a semi-automatic tool for parallelisation of mesh based FORTRAN codes.

Shipping noise in a dynamic sea: a case study of grey seals in the Celtic Sea

Shipping noise is a threat to marine wildlife. Grey seals are benthic foragers, and thus experience acoustic noise throughout the water column, which makes them a good model species for a case study of the potential impacts of shipping noise. We used ship track data from the Celtic Sea, seal track data and a coupled ocean-acoustic modelling system to assess the noise exposure of grey seals along their tracks. It was found that the animals experience step changes in sound levels up to ~20dB at a frequency of 125Hz, and ~10dB on average over 10-1000Hz when they dive through the thermocline, particularly during summer. Our results showed large seasonal differences in the noise level experienced by the seals. These results reveal the actual noise exposure by the animals and could help in marine spatial planning.

Real-time analytics on large dynamic graphs

In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.