Internationalisation of emerging market firms : an exploratory study of Chilean companies

Purpose This paper explores how firms from a Latin American market internationalise using the resource-based view (RBV) of the firm as a theoretical foundation. Specifically, it examines the internationalisation process of three Chilean companies that have become relevant international players. Design/methodology/approach Drawing on interviews with company managers, as well as industry data and corporate reports, this paper provides insights into the successful internationalisation process of emerging market firms. Findings The findings of this study suggest that specific capabilities and resources, such as belonging to a family conglomerate, domestic and foreign partnerships and networks, innovation and market orientation, and an experienced management team, are required for emerging market firms to internationalise and improve their performance in foreign markets. Originality/value This study is one of the few to address the internationalisation process of Chilean companies.

Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN)

The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

The impact of regulatory reforms on the earnings forecasting behaviour of IPO firms

Purpose – The purpose of this paper is to jointly assess the impact of regulatory reform for corporate fundraising in Australia (CLERP Act 1999) and the relaxation of ASX admission rules in 1999, on the accuracy of management earnings forecasts in initial public offer (IPO) prospectuses. The relaxation of ASX listing rules permitted a new category of new economy firms (commitments test entities (CTEs))to list without a prior history of profitability, while the CLERP Act (introduced in 2000) was accompanied by tighter disclosure obligations and stronger enforcement action by the corporate regulator (ASIC). Design/methodology/approach – All IPO earnings forecasts in prospectuses lodged between 1998 and 2003 are examined to assess the pre- and post-CLERP Act impact. Based on active ASIC enforcement action in the post-reform period, IPO firms are hypothesised to provide more accurate forecasts, particularly CTE firms, which are less likely to have a reasonable basis for forecasting. Research models are developed to empirically test the impact of the reforms on CTE and non-CTE IPO firms. Findings – The new regulatory environment has had a positive impact on management forecasting behaviour. In the post-CLERP Act period, the accuracy of prospectus forecasts and their revisions significantly improved and, as expected, the results are primarily driven by CTE firms. However, the majority of prospectus forecasts continue to be materially inaccurate. Originality/value – The results highlight the need to control for both the changing nature of listed firms and the level of enforcement action when examining responses to regulatory changes to corporate fundraising activities.

Predictive compensation for variable network delays and packet losses in networked control systems

Networked control systems (NCSs) offer many advantages over conventional control; however, they also demonstrate challenging problems such as network-induced delay and packet losses. This paper proposes an approach of predictive compensation for simultaneous network-induced delays and packet losses. Different from the majority of existing NCS control methods, the proposed approach addresses co-design of both network and controller. It also alleviates the requirements of precise process models and full understanding of NCS network dynamics. For a series of possible sensor-to-actuator delays, the controller computes a series of corresponding redundant control values. Then, it sends out those control values in a single packet to the actuator. Once receiving the control packet, the actuator measures the actual sensor-to-actuator delay and computes the control signals from the control packet. When packet dropout occurs, the actuator utilizes past control packets to generate an appropriate control signal. The effectiveness of the approach is demonstrated through examples.

Social network analysis of an online dating network

Online social networks can be found everywhere from chatting websites like MSN, blogs such as MySpace to social media such as YouTube and second life. Among them, there is one interesting type of online social networks, online dating network that is growing fast. This paper analyzes an online dating network from social network analysis point of view. Observations are made and results are obtained in order to suggest a better recommendation system for people-to-people networks.

Complexity, evolution, and the structure of demand

This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.

Managing specialised knowledge in technopreneurial firms : evidence from Australian SMEs

This paper analyses particularities of the knowledge management process in technopreneurial firms with particular focus on knowledge identification, acquisition, utilisation and integration. Using a qualitative investigation from a sample of Australian SMEs, a number of key observations are derived which show the challenges of managing knowledge and how important knowledge management is as a management tool for R&D and innovation process in technology-oriented SMEs. Findings suggest that knowledge management and integration processes in these firms are very much project focused and mainly based on ad hoc and informal processes and not embedded within the overall organisational routines.

Using strategic movement to calibrate a neural compass : a spiking network for tracking head direction in rats and robots

The head direction (HD) system in mammals contains neurons that fire to represent the direction the animal is facing in its environment. The ability of these cells to reliably track head direction even after the removal of external sensory cues implies that the HD system is calibrated to function effectively using just internal (proprioceptive and vestibular) inputs. Rat pups and other infant mammals display stereotypical warm-up movements prior to locomotion in novel environments, and similar warm-up movements are seen in adult mammals with certain brain lesion-induced motor impairments. In this study we propose that synaptic learning mechanisms, in conjunction with appropriate movement strategies based on warm-up movements, can calibrate the HD system so that it functions effectively even in darkness. To examine the link between physical embodiment and neural control, and to determine that the system is robust to real-world phenomena, we implemented the synaptic mechanisms in a spiking neural network and tested it on a mobile robot platform. Results show that the combination of the synaptic learning mechanisms and warm-up movements are able to reliably calibrate the HD system so that it accurately tracks real-world head direction, and that calibration breaks down in systematic ways if certain movements are omitted. This work confirms that targeted, embodied behaviour can be used to calibrate neural systems, demonstrates that ‘grounding’ of modeled biological processes in the real world can reveal underlying functional principles (supporting the importance of robotics to biology), and proposes a functional role for stereotypical behaviours seen in infant mammals and those animals with certain motor deficits. We conjecture that these calibration principles may extend to the calibration of other neural systems involved in motion tracking and the representation of space, such as grid cells in entorhinal cortex.

Loop closure detection on a suburban road network using a continuous appearance-based trajectory

This paper presents a novel technique for performing SLAM along a continuous trajectory of appearance. Derived from components of FastSLAM and FAB-MAP, the new system dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM) augments appearancebased place recognition with particle-filter based ‘pose filtering’ within a probabilistic framework, without calculating global feature geometry or performing 3D map construction. For loop closure detection CAT-SLAM updates in constant time regardless of map size. We evaluate the effectiveness of CAT-SLAM on a 16km outdoor road network and determine its loop closure performance relative to FAB-MAP. CAT-SLAM recognizes 3 times the number of loop closures for the case where no false positives occur, demonstrating its potential use for robust loop closure detection in large environments.

From bust to boom : towards a strategic cognition perspective on Australian mining firms’ adaption

While the role of executives’ cognition in organisations’ responses to change is a central topic in strategic cognition research, changes in firms’ environment are typically not measured directly but described either as an event (for example, new industry legislation) or represented by a time period (e.g. when a new technology impacted an industry). The Australian mining sector has witnessed a historically significant change in demand for its products and we begin by developing measures of changes in supply and demand for key commodities during the period 1992-2008. We identify sub-groups of firms based on their activities and commodity sector and examine the relation of these variables to executives’ cognition and to firms’ CapEx. We find industry, firm and cognitive variables are related to both strategic cognition and firms’ CapEx.

Leveraging the network information for evaluating answer quality in a collaborative question answering portal

Collaborative question answering (cQA) portals such as Yahoo! Answers allow users as askers or answer authors to communicate, and exchange information through the asking and answering of questions in the network. In their current set-up, answers to a question are arranged in chronological order. For effective information retrieval, it will be advantageous to have the users’ answers ranked according to their quality. This paper proposes a novel approach of evaluating and ranking the users’answers and recommending the top-n quality answers to information seekers. The proposed approach is based on a user-reputation method which assigns a score to an answer reflecting its answer author’s reputation level in the network. The proposed approach is evaluated on a dataset collected from a live cQA, namely, Yahoo! Answers. To compare the results obtained by the non-content-based user-reputation method, experiments were also conducted with several content-based methods that assign a score to an answer reflecting its content quality. Various combinations of non-content and content-based scores were also used in comparing results. Empirical analysis shows that the proposed method is able to rank the users’ answers and recommend the top-n answers with good accuracy. Results of the proposed method outperform the content-based methods, various combinations, and the results obtained by the popular link analysis method, HITS.

Six degrees of cohesion in patent citation network

While the phrase “six degrees of separation” is widely used to characterize a variety of humanderived networks, in this study we show that in patent citation network, related patents are connected with an average distance of 6, whereas an average distance for a random pair of nodes in the graph is approximately 15. We use this information to improve the recall level in prior-art retrieval in the setting of blind relevance feedback without any textual knowledge.

The development of a conceptual framework for a district 4-Year Pavement Management Plan, implementation of network-level project screening process

The Texas Department of Transportation (TxDOT) is concerned about the widening gap between preservation needs and available funding. Funding levels are not adequate to meet the preservation needs of the roadway network; therefore projects listed in the 4-Year Pavement Management Plan must be ranked to determine which projects should be funded now and which can be postponed until a later year. Currently, each district uses locally developed methods to prioritize projects. These ranking methods have relied on less formal qualitative assessments based on engineers’ subjective judgment. It is important for TxDOT to have a 4-Year Pavement Management Plan that uses a transparent, rational project ranking process. The objective of this study is to develop a conceptual framework that describes the development of the 4-Year Pavement Management Plan. It can be largely divided into three Steps; 1) Network-Level project screening process, 2) Project-Level project ranking process, and 3) Economic Analysis. A rational pavement management procedure and a project ranking method accepted by districts and the TxDOT administration will maximize efficiency in budget allocations and will potentially help improve pavement condition. As a part of the implementation of the 4-Year Pavement Management Plan, the Network-Level Project Screening (NLPS) tool including the candidate project identification algorithm and the preliminary project ranking matrix was developed. The NLPS has been used by the Austin District Pavement Engineer (DPE) to evaluate PMIS (Pavement Management Information System) data and to prepare a preliminary list of candidate projects for further evaluation.

Tunable decoupling and matching network for diversity enhancement of closely spaced antennas

A tunable decoupling and matching network (DMN) for a closely spaced two-element antenna array is presented. The DMN achieves perfect matching for the eigenmodes of the array and thus simultaneously isolates and matches the system ports while keeping the circuit small. Arrays of closely spaced wire and microstrip monopole pairs are used to demonstrate the proposed DMN. It is found that monopoles with different lengths can be used for the design frequency by using this DMN, which increases the design flexibility. This property also enables frequency tuning using the DMN only without having to change the length of the antennas. The proposed DMN uses only one varactor to achieve a tuning range of 18.8% with both return loss and isolation better than 10-dB when the spacing between the antenna is 0.05λ. When the spacing increases to 0.1λ, the simulated tuning range is more than 60%.

Optimising a coal rail network under capacity constraints

This research deals with an innovative methodology for optimising the coal train scheduling problem. Based on our previously published work, generic solution techniques are developed by utilising a “toolbox” of standard well-solved standard scheduling problems. According to our analysis, the coal train scheduling problem can be basically modelled a Blocking Parallel-Machine Job-Shop Scheduling (BPMJSS) problem with some minor constraints. To construct the feasible train schedules, an innovative constructive algorithm called the SLEK algorithm is proposed. To optimise the train schedule, a three-stage hybrid algorithm called the SLEK-BIH-TS algorithm is developed based on the definition of a sophisticated neighbourhood structure under the mechanism of the Best-Insertion-Heuristic (BIH) algorithm and Tabu Search (TS) metaheuristic algorithm. A case study is performed for optimising a complex real-world coal rail system in Australia. A method to calculate the lower bound of the makespan is proposed to evaluate results. The results indicate that the proposed methodology is promising to find the optimal or near-optimal feasible train timetables of a coal rail system under network and terminal capacity constraints.