计量经济分析 = Econometric analysis

The Uppsala internationalization process model is revisited in the light of changes in business practices and theoretical advances that have been made since 1977. Now the business environment is viewed as a web of relationships, a network, rather than as a neoclassical market with many independent suppliers and customers. Outsidership, in relation to the relevant network, more than psychic distance, is the root of uncertainty. The change mechanisms in the revised model are essentially the same as those in the original version, although we add trust-building and knowledge creation, the latter to recognize the fact that new knowledge is developed in relationships.

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The Uppsala Internationalization Process Model Revisited: From Liability of Foreignness to Liability of Outsidership

How have Japanese companies become world leaders in the automotive and electronics industries, among others? What is the secret of their success? Two leading Japanese business experts, Ikujiro Nonaka and Hirotaka Takeuchi, are the first to tie the success of Japanese companies to their ability to create new knowledge and use it to produce successful products and technologies. In The Knowledge-Creating Company, Nonaka and Takeuchi provide an inside look at how Japanese companies go about creating this new knowledge organizationally. The authors point out that there are two types of knowledge: explicit knowledge, contained in manuals and procedures, and tacit knowledge, learned only by experience, and communicated only indirectly, through metaphor and analogy. U.S. managers focus on explicit knowledge. The Japanese, on the other hand, focus on tacit knowledge. And this, the authors argue, is the key to their success--the Japanese have learned how to transform tacit into explicit knowledge. To explain how this is done--and illuminate Japanese business practices as they do so--the authors range from Greek philosophy to Zen Buddhism, from classical economists to modern management gurus, illustrating the theory of organizational knowledge creation with case studies drawn from such firms as Honda, Canon, Matsushita, NEC, Nissan, 3M, GE, and even the U.S. Marines. For instance, using Matsushita's development of the Home Bakery (the world's first fully automated bread-baking machine for home use), they show how tacit knowledge can be converted to explicit knowledge: when the designers couldn't perfect the dough kneading mechanism, a software programmer apprenticed herself withthe master baker at Osaka International Hotel, gained a tacit understanding of kneading, and then conveyed this information to the engineers. In addition, the authors show that, to create knowledge, the best management style is neither top-down nor bottom-up, but rather what they call "middle-up-down," in which the middle managers form a bridge between the ideals of top management and the chaotic realities of the frontline. As we make the turn into the 21st century, a new society is emerging. Peter Drucker calls it the "knowledge society," one that is drastically different from the "industrial society," and one in which acquiring and applying knowledge will become key competitive factors. Nonaka and Takeuchi go a step further, arguing that creating knowledge will become the key to sustaining a competitive advantage in the future. Because the competitive environment and customer preferences changes constantly, knowledge perishes quickly. With The Knowledge-Creating Company, managers have at their fingertips years of insight from Japanese firms that reveal how to create knowledge continuously, and how to exploit it to make successful new products, services, and systems.

The knowledge-creating company

The 2008 crash has left all the established economic doctrines - equilibrium models, real business cycles, disequilibria models - in disarray. Part of the problem is due to Smith’s "veil of ignorance": individuals unknowingly pursue society’s interest and, as a result, have no clue as to the macroeconomic effects of their actions: witness the Keynes and Leontief multipliers, the concept of value added, fiat money, Engel’s law and technical progress, to name but a few of the macrofoundations of microeconomics. A good viewpoint to take bearings anew lies in comparing the post-Great Depression institutions with those emerging from Thatcher and Reagan’s economic policies: deregulation, exogenous vs. endoge- nous money, shadow banking vs. Volcker’s Rule. Very simply, the banks, whose lending determined deposits after Roosevelt, and were a public service became private enterprises whose deposits determine lending. These underlay the great moderation preceding 2006, and the subsequent crash.

The Economic Institutions of Capitalism

Knowledge sharing: A review and directions for future research

The rapid increase of traffic data generated by different sensing systems opens many opportunities to improve transportation services. An important opportunity is to enable stochastic routing that computes the arrival time probabilities for each suggested route instead of only the expected travel time. However, traffic datasets typically have many missing values, which prevents the construction of stochastic speeds. To address this limitation, we propose the Stochastic Spatio-Temporal Graph Convolutional Network (SST-GCN) architecture that accurately imputes missing speed distributions in a road network. SST-GCN combines Temporal Convolutional Networks and Graph Convolutional Networks into a single framework to capture both spatial and temporal correlations between road segments and time intervals. Moreover, to cope with datasets with many missing values, we propose a novel self-adaptive context-aware diffusion process that regulates the propagated information around the network, avoiding the spread of false information. We extensively evaluate the effectiveness of SST-GCN on real-world datasets, showing that it achieves from 4.6% to 50% higher accuracy than state-of-the-art baselines using three different evaluation metrics. Furthermore, multiple ablation studies confirm our design choices and scalability to large road networks.

Spatio-temporal graph convolutional network for stochastic traffic speed imputation

Global Strategy Journal second launch issue: comments from the co‐editors

Research Summary In this second collection of articles relating to global strategy, we address the well-established but unresolved issue of the relationship between multinationality and performance among multinational firms. The M-P relationship has been the topic of many articles in many journals for many years, but its true nature is still not established. Both theory and empirical findings provide different and often opposed views, as can be seen in the articles collected here. We see two main perspectives on this issue. Some scholars suggest that differences in data and analytical tools have prevented consistent empirical results, and that more consistent and carefully chosen empirical modeling can yet establish the true M-P connection. Others believe that basic problems in theory and in building testable frameworks that are truly consistent with theory have made this an inherently intractable problem. The collection provides important articles that test the M-P relationship as well as critiques from both perspectives. We see considerable power in the view that individual firms are likely to have their own idiosyncratic optimal level of multinationaliation. We finish by calling for and suggesting new approaches to the issue, such as a micro-foundations approach, as opposed to simply using more sophisticated tools to test problematic models based on well-established but ultimately inadequate theory. Managerial Summary The relationship between the level of multinational diversification and performance in multinational firms is at the heart of global strategy. If operating at ever increasing levels in ever more countries does not provide reliably superior performance, why do firms continue to expand internationally? One view suggests that since firms continue to increase their international presence, there must be some ultimate benefits—difficult as they may be to establish. The opposing view suggests that since an equal amount of research finds no such benefits, it may be that no level of multinational diversification is generally optimal, but that depending on its particular resources and capabilities, experience, industry, and national portfolio, each multinational must discover its own optimal level of cross-border investment. 

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/gsj.1478

Global strategy collections: Multinationality and performance

Taking inspiration from linguistics, the communications theoretical community has recently shown a significant recent interest in pragmatic , or goal-oriented, communication. In this paper, we tackle the problem of pragmatic communication with multiple clients with different, and potentially conflicting, objectives. We capture the goal-oriented aspect through the metric of Value of Information (VoI), which considers the estimation of the remote process as well as the timing constraints. However, the most common definition of VoI is simply the Mean Square Error (MSE) of the whole system state, regardless of the relevance for a specific client. Our work aims to overcome this limitation by including different summary statistics, i.e., value functions of the state, for separate clients, and a diversified query process on the client side, expressed through the fact that different applications may request different functions of the process state at different times. A query-aware Deep Reinforcement Learning (DRL) solution based on statically defined VoI can outperform naive approaches by 15-20%.

Goal-Oriented Scheduling in Sensor Networks with Application Timing Awareness

Abstract To ensure critical infrastructure is operating as expected, high-quality sensors are increasingly installed. However, due to the enormous amounts of high-frequency time series they produce, it is impossible or infeasible to transfer or even store these time series in the cloud when using state-of-the-practice compression methods. Thus, simple aggregates, e.g., 1–10-minutes averages, are stored instead of the raw time series. However, by only storing these simple aggregates, informative outliers and fluctuations are lost. Many Time Series Management System (TSMS) have been proposed to efficiently manage time series, but they are generally designed for either the edge or the cloud. In this paper, we describe a new version of the open-source model-based TSMS ModelarDB. The system is designed to be modular and the same binary can be efficiently deployed on the edge and in the cloud. It also supports continuously transferring high-frequency time series compressed using models from the edge to the cloud. We first provide an overview of ModelarDB, analyze the requirements and limitations of the edge, and evaluate existing query engines and data stores for use on the edge. Then, we describe how ModelarDB has been extended to efficiently manage time series on the edge, a novel file-based data store, how ModelarDB’s compression has been improved by not storing time series that can be derived from base time series, and how ModelarDB transfers high-frequency time series from the edge to the cloud. As the work that led to ModelarDB began in 2015, we also reflect on the lessons learned while developing it. 

/pdf/modelardb-integrated-model-based-management-of-time-series-1an9ypcy.pdf

Torben Pedersen

Papers

Spatio-temporal graph convolutional network for stochastic traffic speed imputation

Global Strategy Journal second launch issue: comments from the co‐editors

Global strategy collections: Multinationality and performance

Goal-Oriented Scheduling in Sensor Networks with Application Timing Awareness

ModelarDB: Integrated Model-Based Management of Time Series from Edge to Cloud