Measuring business cycle turning points in Japan with the Markov Switching Panel model

This paper employs a Markov Switching Panel model to measure business cycle turning points in Japan. This Markov Switching Panel model is simple and can easily be estimated following Hamilton's [J.D. Hamilton, A new approach to the economic analysis of nonstationary time series and the business cycle, Econometrica 57 (1989) 357–384] method. We find that this model is highly capable of identifying Japanese recessionary dates, and it also has a forecast performance that is equal to that of the Markov Switching Vector Autoregressive model. The implication that emerges here is that governments, their agencies and other business leaders in Japan and elsewhere should also employ the Markov Switching Panel model to secure complementary data.     

Testing for expected return and market price of risk in Chinese A and B share markets: A geometric Brownian motion and multivariate GARCH model approach

There exist dual listed stocks which are issued by the same company in some stock markets. Although these stocks bare the same firm-specific risks and enjoy identical dividends and voting policies, they are priced differently. Some previous studies show this seeming deviation from the law of one price can be solved by allowing different expected returns and market prices of risk for investors holding heterogeneous beliefs. This paper provides empirical evidence for that argument by testing the expected return and market price of risk between Chinese A and B shares listed in Shanghai and Shenzhen stock markets. Models with dynamic of Geometric Brownian Motion are adopted. Multivariate GARCH models are also introduced to capture the feature of time-varying volatility in stock returns. The results suggest that the different pricing can be explained by the difference in expected returns between A and B shares. However, the difference between market price of risk is insignificant for both markets if GARCH models are adopted.     

Volatility spillovers, interdependence and comovements: A Markov Switching approach

The transmission mechanisms of volatility between markets can be characterized within a new Markov Switching bivariate model where the state of one variable feeds into the transition probability of the state of the other. A number of model restrictions and hypotheses can be tested to stress the role of one market relative to another (spillover, interdependence, comovement, independence, Granger noncausality). The model is estimated on the weekly high-low range of five Asian markets, assuming a central (but not necessarily dominant) role for Hong Kong. The results show plausible market characterizations over the long run with a spillover from Hong Kong to Korea and Thailand, interdependence with Malaysia and comovement with Singapore.     

Measuring the functional dynamics of product-service system: A system dynamics approach

In the light of the prevailing trend towards product-service systems (PSSs), this paper focuses on the measurement of PSS functional performance. As a ‘dynamic’ system wherein various stakeholders achieve functional performance through long-term relationships in a complex value network, PSS functional performance requires a dynamic approach for measuring its effectiveness, an approach that is missing in the literature. This study aims to fill that void. Firstly, we address the concept of functional dynamics as a distinctive measure of PSS functionality with regard to functional performance and propose a five-phase analytic scheme of functional dynamics. Then, to measure the functional dynamics of PSS using the analytic scheme, a four-step procedure based on the system dynamics is suggested. As a representative method for measuring the long-term dynamics of a complex system, system dynamics is effectively employed to measure PSS’s functional dynamics comprehensively. To illustrate the proposed approach, a case study of a u-healthcare system is presented.     

Modelling and forecasting short-term load demand: A multivariate approach

A multivariable time series model is proposed for short-term load demand forecasting. Unlike other approaches, the order of the model is determined without first finding the coefficients of the model. The Hankel matrix used for determining the order is also utilized for estimating the parameters of the model. This is then compared with order determination using the AIC criterion. Actual data provided by the Ontario Hydro for four loading buses is used for five-minute and hourly forecasts. The results show that the proposed approach is very attractive.     

A new approach to the symbolic factorization of multivariate polynomials

A heuristic factorization scheme that uses learning and other heuristic programming techniques to improve the efficiency of determining the symbolic factorization of multivariate polynomials with integer coefficients and an arbitrary number of variables and terms is described. The learning program, POLYFACT, in which the factorization scheme is implemented is also described. POLYFACT uses learning through the dynamic construction and manipulation of first-order predicate calculus heuristics to reduce the amount of searching for the irreducible factors of a polynomial.Tables containing the results of factoring randomly generated multivariate polynomials are presented: (1) to demonstrate that learning does improve considerably the efficiency of factoring polynomials, and (2) to show that POLYFACT does learn from previous experience.The factorization times of polynomials factored by both the scheme implemented in POLYFACT and Wang's implementation of Berlekamp's algorithm are given. The two algorithms are compared, and two situations where POLYFACT'S algorithm can be used to improve the efficiency of Wang's algorithm are discussed.     

ESAS: A case-based approach to business planning and monitoring

Abstract: Creating and sustaining a competitive advantage in today’s turbulent world markets is a formidable business challenge. For many organisations, operating within an inherently unstable external environment has resulted in the need for a cultural rethink. Business complacency, brought about by corporate industry monopolisation, the reliance on reputation, brand identity, and customer allegiance, is no longer a recipe for sustained market growth. Companies have realised that being market focused could provide them with a competitive edge within the marketplace. To achieve this organisations have turned to the ‘Quality movement’, embracing the Total Quality Management (TQM) philosophy and its inherent tools (auditing frameworks, concept of quality systems etc.) as a means to recapture lost ground. ESAS ( E nterprise S trategic A dvisory S ystem) is a prototype intelligent system that utilises a case- based approach to address the issues raised above, by providing organisations with advice on market- led quality and competitive strategy. This paper explores the philosophy and ideas behind the ESAS concept, and describes the development of an ESAS prototype.     

Real-time risk monitoring in business processes: A sensor-based approach

This article proposes an approach for real-time monitoring of risks in executable business process models. The approach considers risks in all phases of the business process management lifecycle, from process design, where risks are defined on top of process models, through to process diagnosis, where risks are detected during process execution. The approach has been realized via a distributed, sensor-based architecture. At design-time, sensors are defined to specify risk conditions which when fulfilled, are a likely indicator of negative process states (faults) to eventuate. Both historical and current process execution data can be used to compose such conditions. At run-time, each sensor independently notifies a sensor manager when a risk is detected. In turn, the sensor manager interacts with the monitoring component of a business process management system to prompt the results to process administrators who may take remedial actions. The proposed architecture has been implemented on top of the YAWL system, and evaluated through performance measurements and usability tests with students. The results show that risk conditions can be computed efficiently and that the approach is perceived as useful by the participants in the tests.     

Evaluation of inter-organizational business process solutions: A conceptual model-based approach

Collaboration and coordination between organizations are necessary in today’s business environment, and are enabled by inter-organizational processes. Many approaches for the construction of such processes have been proposed in recent years. However, due to the lack of standard terminology it is hard to evaluate and select a solution that fits a specific business scenario. The paper proposes a conceptual model which depicts the nature of interaction between organizations through business processes under specific business requirements that emphasize the privacy and autonomy of the participating organizations. The model is generic, and relies on the generic process model (GPM) framework and on Bunge’s ontology. Being generic and theory-based, we propose to use the model as a basis for comparing and evaluating design and implementation-level approaches for inter-organizational processes. We demonstrate the evaluation procedure by applying it to three existing approaches.

Principles of work system performance optimization: A business ergonomics approach

Recently, there has been a growing interest in optimizing performance in the workplace. This interest is stimulated not only by economic and competitive pressures, but also by a growing awareness of the need to improve health and safety, thereby improving workplace wellness and vitality and, in turn, productivity. This article reviews the contributions of traditional approaches to work system performance optimization. These approaches include scientific management, work-time studies, industrial psychology, ergonomics, human factors, industrial engineering, total quality management, kaizen theory, systems theory, and operations research. The benefits, features, and drawbacks of each approach are discussed and tabulated. A basis for a new comprehensive methodology of work system performance optimization called the business ergonomics approach is then outlined and presented. © 1999 John Wiley & Sons, Inc.     

Examining the state of empirical business intelligence and analytics research: A poly-theoretic approach

Interest in Business Intelligence and Analytics (BI&A) has led to a growing body of impactful scholarly articles. We investigate the state of BI&A research by answering what is the state of BI&A research in terms of constructs studied, article's macrostructure, and theoretical contributions, and how do the constructs studied, macrostructure, and theoretical contributions, influence an article's impact? We propose a poly-theoretic framework that classifies articles from top IS journals and conferences by studied construct, macrostructure, contribution, distribution, and impact. Findings provide an understanding of how articles’ components influence the impact of BI&A research. Implications and future research areas are discussed.     

Finder: A novel approach of change point detection for multivariate time series

The multivariate time series often contain complex mixed inputs, with complex correlations between them. Detecting change points in multivariate time series is of great importance, which can find anomalies early and reduce losses, yet very challenging as it is affected by many complex factors, i.e., dynamic correlations and external factors. The performance of traditional methods typically scales poorly. In this paper, we propose Finder, a novel approach of change point detection via multivariate fusion attention networks. Our model consists of two key modules. First, in the time series prediction module, we employ multi-level attention networks based on the Transformer and integrate the external factor fusion component, achieving feature extraction and fusion of multivariate data. Secondly, in the change point detection module, a deep learning classifier is used to detect change points, improving efficiency and accuracy. Extensive experiments prove the superiority and effectiveness of Finder on two real-world datasets. Our approach outperforms the state-of-the-art methods by up to 10.50% on the F1 score.

     

Governing the teak furniture business: A global value chain system dynamic modelling approach

Javanese teak forest constitutes more than 35% of world teak forests. It provides employment and livelihood to millions of people. This paper describes the use of systems dynamics to mimic the value chain of teak from forest to final furniture market using phases of conceptual design, model specification, model evaluation and model uses. The model comprises Perhutani plantation teak, community agroforest, teak log trading, furniture manufacturing and market. From the model we observe baseline trends of teak forest and incomes to various actors participating in teak business including forest state enterprise Perhutani, local communities, brokers, manufacturers and retailers. We use the model to produce governance scenarios of fair trade and vertical integration, their impacts on actors' income and the sustainability of teak plantations.     

A behavioral approach of the dynamics of financial markets

We introduce a non-linear dynamic deterministic multistocks multi-agents model. The model can be viewed as the centre of a decision support system in managing financial portfolios, that would allow the decision maker to formalize, test and analyze the impacts of strategies on a market. It takes into account explicitly the perceptions, strategies and decisions of actors and their actions on a market. This approach attempts to model the decision process of interacting agents and so furnishes a tool for decision making in order to analyze the impacts of various strategies of actors on a market. Even in this simple model, the non-linear interactions can drive the system to sudden and unexpected effects which shows the importance of the attempt of the understanding of the dynamics.     

A semantic repository approach to improve the government to business relationship

A major objective in business interactions consists in enhancing the business perspective over service provision by developing strategies and tools to provide support in the selection of services according to the value they have for businesses. This means providing a way to determine the value of services according to specific business criteria, and conceive technologies that support the sharing of knowledge involved in service provision. In this paper we present an approach based on semantic repositories. The repository enables a business perspective over service provision, based on the association between services and business processes, and is related to the problem of supporting businesses in the value-driven service selection. This perspective is addressed in the paper by exploiting expressive semantic representations and reasoning. An ontology for representing relevant semantic properties of services and processes is provided, and an algorithm for value-based service selection is presented. Two real life case studies show the effectiveness of the approach.     

Understanding life cycle social impacts in manufacturing: A processed-based approach

Developing sustainable products and processes is growing in importance due to increasing regulation, consumer interest, access to information, and competitive forces. In order to adequately evaluate the sustainability of products and processes, there is a need to consider the impacts from all three pillars of sustainability – society, environment, and economics. There are substantial challenges to identifying and understanding the social impacts associated with manufacturing activities. This paper provides a framework for characterizing the social impacts of manufacturing throughout the life cycle of a product or process. Social impacts occur on various scales in manufacturing, from the level of a unit process to the level of the enterprise. Additionally, manufacturing activities impact consumers, communities, and larger political/spatial realms. This paper identifies key characteristics of social impacts associated with manufacturing that should be considered to more effectively address the social dimension of sustainability for products and processes. Examples involving a typical manufacturing process – welding – are presented to illustrate the utility of the framework.     

A business model for deploying Web services:A data-centric approach based on factual dependencies

The standards XML, SOAP, WSDL and UDDI allow (i) services to be accessed and executed via the Web; and (ii) a loose coupling of these services. Thanks to these standards, Web services technology is becoming not only a de facto integration standard, but also a de facto Internet standard instance of the SOA architecture. However, the deployment of such a technology is still hindered by some technical as well as methodological issues. This paper proposes a business model with multiple interfaced abstraction levels as a framework to methodologically deploy Web services technology with respect to SOA architecture. The attributes describing the business objects and coordination artifacts as described in the highest abstraction level of the business model, i.e. the universe of discourse, are aggregated according to a time/space constraint called factual dependency. Each aggregation of factually dependent attributes is validated with regard to an actual business event. The aggregation is then interfaced to lead to a well-specified Web service. The resulting comprehensive set of consistent Web services are then registered in a public or a private UDDI to be discovered and invoked by any business process. The proposed Web services generation process aims at unlocking and turning informational assets into actions. It differs from the current IT perspective approaches that generate Web services directly from redundant and inconsistent elements in the enterprise information systems.     

A population dynamics approach for the water distribution problem

The water distribution system (WDS) is composed of several elements, where flow control is one of the most important components needed in order to provide a satisfactory level of service. In order to achieve an adequate level of water in the distribution tanks, we need to dynamically control the flow. Here, we propose a population dynamics approach in order to control tanks, by allocating in them the maximum uniform volume. The feedback interconnected systems reach a stable equilibrium point for both approaches presented (i.e. replicator and supply dynamics), and more specific an asymptotically stable equilibrium point for the replicator dynamics case. The stability analysis uses some passivity concepts and classic Lyapunov theory for a closed-loop system that combines the population dynamics (controller), and the WDS (process). We show via simulations the operation under different scenarios.     

Joint modelling of multivariate longitudinal outcomes and a time-to-event: A nonlinear latent class approach

A joint model based on a latent class approach is proposed to explore the association between correlated longitudinal quantitative markers and a time-to-event. A longitudinal latent class model describes latent profiles of evolution of the latent process underlying the correlated markers. The latent process is linked to the markers by nonlinear transformations including parameters to be estimated. A proportional hazard model describes the joint risk of event according to the latent classes and two specifications of the risk function are considered: a parametric function and a semi-parametric function based on splines. Depending on the chosen risk function, estimation is performed by a maximum likelihood or a maximum penalized likelihood approach. A simulation study validates the estimation procedure. As a latent class model relies on the strong assumption that the markers and the time-to-event are independent conditionally on the latent classes, a test of conditional independence is proposed using the residuals conditional on time-to-event. The procedure does not require any posterior classification and can be conducted using standard statistical softwares. The methodology is applied to describe profiles of cognitive decline in the elderly and their associated risk of dementia.     

A modular approach to the dynamics of complex multirobot systems

This work presents a modular approach for the dynamic modeling and efficient simulation of complex robot systems composed of multiple robots constrained by multiple concurrent contacts. The modular nature of the algorithm enables existing open-chain models for individual robots and other mechanisms to be incorporated without significant reprogramming, while a general contact model allows both holonomic and nonholonomic constraints in the system. An example is provided to illustrate the algorithm's modularity and demonstrate its application. In addition to the development of the dynamic equations, this paper will discuss the implementation of the simulation algorithm in detail, including issues of computational complexity.