Information technology for collaborative advantage in healthcare revisited

Interorganizational systems are expected to provide opportunities for various stakeholders, often competitors, to collaborate. At the moment, there is a great need for research evidence on the factors facilitating or impeding the achievement of collaborative advantage between interorganizational systems stakeholders. A recent contribution has been the use of a health-information network case to derive lessons for policy makers in this respect. The development and use of the NHSnet in the United Kingdom provides an opportunity to review these lessons in a different context of health-information exchange. Combined with the use of stakeholder analysis, these lessons can enhance our understanding of the context, the stakeholders involved and affected by the network, their interests and their perceptions of collaborative advantage. It, therefore, provides useful insights in the lessons that healthcare policy makers can apply in the development and use of a collaborative network. Further theoretical and practical research is, however, needed to improve our understanding of success and failure factors for the achievement of collaborative advantage in different environments.     

A Theory of Constraints approach to interorganizational systems implementation

Interorganizational systems (IOS) may provide substantial benefits, however many organizations are reluctant to implement them. This empirical research takes a novel approach and develops a model of IOS feasibility, which is based on the Theory of Constraints (TOC). It introduces the notion of maximal infeasibility, which is the highest among the values of five factors: economic infeasibility, organizational infeasibility, technological infeasibility, risks, and lack of financial resources. The highest value was selected because implementation is hindered even if only one of the feasibility requirements is not fulfilled. Data collected from 139 medium and large Israeli business organizations validated the model, and indicated that strategic motivation is the main driving force for an organization to initiate or to join an IOS, while the main barriers are organizational infeasibility issues such as lack of management support or uninterested potential partners. Adopting a TOC approach to IOS implementation may assist organizations to overcome these obstacles and increase the chance of a successful implementation. An earlier shorter version of this paper was presented at WEB 2006, a pre-ICIS workshop on e-business, in Milwaukee, WI.     

Relative importance,specific investment and ownership in interorganizational systems

Implementation and maintenance of interorganizational systems (IOS) require investments by all the participating firms. Compared with intraorganizational systems, however, there are additional uncertainties and risks. This is because the benefits of IOS investment depend not only on a firm’s own decisions, but also on those of its business partners. Without appropriate levels of investment by all the firms participating in an IOS, they cannot reap the full benefits. Drawing upon the literature in institutional economics, we examine IOS ownership as a means to induce value-maximizing noncontractible investments. We model the impact of two factors derived from the theory of incomplete contracts and transaction cost economics: relative importance of investments and specificity of investments. We apply the model to a vendor-managed inventory system (VMI) in a supply chain setting. We show that when the specificity of investments is high, this is a more critical determinant of optimal ownership structure than the relative importance of investments. As technologies used in IOS become increasingly redeployable and reusable, and less specific, the relative importance of investments becomes a dominant factor. We also show that the bargaining mechanism—or the agreed upon approach to splitting the incremental payoffs—that is used affects the relationship between these factors in determining the optimal ownership structure of an IOS.

Defining stakeholder involvement in participatory design processes

A participatory approach could be used to implement work place or organizational improvements. However, the question is which participants should be involved and how. In this paper the theoretical involvement in different steps of a linear stepwise approach is described and compared with the latest projects of 300 practitioners.

From a theoretical point of view ergonomists and employees play an essential role in the improvement process and are involved in most stages of a change process. Designers play an important role in idea generation and prototyping. Top management and middle management are important in the first step to set goals that are consistent with the strategy of the enterprise. Middle management is also needed in the steps where improvements are selected.

This theoretical prediction is affirmed. However, middle management appeared to be also involved in implementation. The role of ergonomists is in practice limited in later stages in implementation, which is not preferred by the ergonomists.     

Lessons learned from three interorganizational health care information systems

The airline, financial, retail, consumer goods and cotton industries are not alone in their increased use of interorganizational information systems (IOSs). Health care organizations are investing and participating in a growing number of IOSs, such as community health information networks (CHINs) and integrated delivery systems (IDS). This paper examines the experiences of three CHIN systems located in the US — Midwest. Multiple data sources, including executive interviews, memoranda, internal documentation and system demonstrations, provided data for this research. The history of each case provides a better understanding of systems implementation and the underlying determinants that emerged as having significant impact. Not only do these findings provide guidelines and learning tools for practitioners, but they also hold implications to the field and its current position on bipolar streams in the literature. Lastly, our findings suggest that large health care infrastructures will continue to be confronted by the presence of the World Wide Web and electronic commerce.     

A neurofuzzy methodology for impedance-based multiphase flow identification

A neurofuzzy methodology for flow identification based on signals obtained from an impedance void meter is presented. The methodology combines the filtering and interpolative capabilities of neural networks with the representational advantages of fuzzy systems for the purpose of mapping idiosyncratic area-averaged impedance measurements to multiphase flow regimes. It has been shown that electrical signals representing the conductance of the intervening medium can be used to infer crucial flow parameters, and that area-averaged signals contain sufficient information about flow regime and the structure of its two-phase constituents. The neurofuzzy approach is a promising means for reconstructing the visual imagery of flow in a process, analogous to tomography, and holds considerable promise for multiphase flow diagnostic and measurement applications in the nuclear as well as in the petroleum, biomedical, and food-processing industries.     

GIS-based decision support for solar energy planning in urban environments

This paper describes the development of a solar energy planning system, consisting of a methodology and decision support software for planners and energy advisers. Intended primarily to predict and realise the potential of solar energy on an urban scale, the system will support decisions in relation to the key solar technologies: solar water heating, photovoltaics and passive solar gain. The prototype discussed here relates to the first of these. Based on a methodology for predicting the solar energy potential of domestic housing stock, it is implemented as a relational database application linked to a customised geographical information system (GIS). The methodology takes into account baseline energy consumption and projected energy saving benefits. To support this, the system incorporates a domestic energy model and addresses the major problem of data collection in two ways. Firstly, it provides a comprehensive set of default values derived from a new dwelling classification scheme that builds on previous research. Secondly, novel GIS tools enable key data to be extracted from digital urban maps in different operational modes. The paper concludes with a discussion of possible planning scenarios to illustrate how the system may be deployed at various levels of granularity to assist targeting of individual properties or city neighbourhoods, or for whole-city projections.     

Information management for integrated design environments

This paper identifies requirements for an engineering design information management system. Future CAD systems must support a wide range of activities — such as definition, manipulation and analyses of complex product information models. These models represent not only conventional data associated with current CAD applications, but also design information characterizing the correlations between the requirements, functions, behaviors and physical form of the product. Such functionality is important for both the individual designer and the design organization, as the need to manage information as a corporate asset is becoming a critical component of business strategy. This paper explores these needs using two design studies. The first study illustrates some major concepts relative to non-routine design activities, while the second study focuses on the routine design activities relative to organization interactions. These studies were used to elicit high level requirements which serve as the basis for the development of prototype software systems. These prototypes are briefly introduced here.     

Knowledge sharing in cross-boundary information system development in the public sector

The success of information system development involving multi-organizational collaboration can depend heavily on effective knowledge sharing across boundaries. This paper reports on a comparative examination of knowledge sharing in two separate networks of public sector organizations participating in information technology innovation projects in New York State. As is typical of innovations resulting from recent government reforms, the knowledge sharing in these cases is a critical component of the information system development, involving a mix of tacit, explicit, and interactional forms of sharing across organizational boundaries. In one case the sharing is among state agencies and in the other across state and local government agencies. Using interviews, observations and document analysis, the longitudinal case studies follow knowledge sharing and other interactions in the interorganizational networks of these two distinct settings. Results confirm the difficulty of sharing knowledge across agencies, and further reveal the influences of several relevant factors—incentives, risks and barriers for sharing, and trust—on the effectiveness of knowledge sharing. The results contribute to theory on knowledge sharing processes in multi-organizational public sector settings and provide practice guidance for developing effective sharing relationships in collaborative cross-boundary information system initiatives. The research reported here is supported by the National Science Foundation grant #SES-9979839. The views and conclusions expressed in this report are those of the authors alone and do not reflect the views or policies of the National Science Foundation.     

An information age opportunity — Providing information for customers

Evolutionary growth of the use of information technology in business operations now provides a new information-age opportunity for managers, that of providing information for customers (PIC). In the PIC applications, information is a product not a resource and the product is information, not data. Pertinent examples of firms using PIC and steps to be taken by any firm that desires to implement this concept are explained in some detail. This application of computer technology usually can be implemented at minimal costs. PIC provide competitive advantages to the firm by tangibilizing various information services for customers.     

Trust, power and interorganizational information systems: the case of the electronic trading community TransLease

This paper focuses on Cap Gemini’s electronic commerce system, TransLease. TransLease is an interorganizational information system (IOS), which facilitates electronic commerce between motor vehicle leasing and repair companies. During our investigation, the system was used by approximately 1000 repair agents working for seven of the UK’s leading vehicle leasing and contract hire companies. This system was originally developed by AT&T and acquired by Cap Gemini in July 1998. At the time of acquisition, the system was seen as being of high strategic value, although it was also seen as underperforming. This paper reports the results of an action research project, which formed one element of the process by which Cap Gemini investigated the former problem. In the paper, TransLease is described as a complex electronic community, dependent upon the existence of symbiotic relationships. As such, the problems that the system users and developers experienced can be attributed to factors that impeded the mutual benefit accruing from participation in the system. The efficacy of the terms of exchange and the degree to which participants mutually benefit through electronic interaction is determined by the complex interplay of a number of relational and organizational factors. The research therefore illustrates the importance of the ‘soft’ organizational issues in IOS management and development, and suggests a conceptual model of the factors relevant in this case. At the time of this study, TransLease was still in the early stages of its life cycle, having only been available in the marketplace for approximately 18 months. During this time, through recognizing the complex problems and issues detailed in this paper, Cap Gemini accordingly redressed the way in which the system was managed and maintained. TransLease is now seen as having matured into a highly successful example of an IOS – a view reflected by its position as market leader in the industry. As this paper will show, the key to improving the existing service has been the emphasis Cap Gemini now places on managing the ‘soft’ aspects of the electronic community.     

An Optimized Method for Accounting Information in Logistic Systems

In the era of rapid information development, with the popularity of computers, the advancement of science and technology, and the ongoing expansion of IT technology and business, the enterprise resource planning (ERP) system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations. Because of developments in information technology, most manual accounting procedures are being replaced by computerized Accounting Information Systems (AIS), which are quicker and more accurate. The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS. This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree. The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response. Furthermore, the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements. Using the three ways of marginal revenue, marginal cost, and business matching degree, the information with cumulative weights is which is deployed to form the data from the intersection of the best order. It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.     

Recurrent type-2 fuzzy neural network using Haar wavelet energy and entropy features for speech detection in noisy environments

This paper proposes a new method to detect the boundary of speech in noisy environments. This detection method uses Haar wavelet energy and entropy (HWEE) as detection features. The Haar wavelet energy (HWE) is derived by using the robust band that shows the most significant difference between speech and nonspeech segments at different noise levels. Similarly, the wavelet energy entropy (WEE) is computed by selecting the two wavelet energy bands whose entropy shows the most significant speech/nonspeech difference. The HWEE features are fed as inputs to a recurrent self-evolving interval type-2 fuzzy neural network (RSEIT2FNN) for classification. The RSEIT2FNN is used because it uses type-2 fuzzy sets, which are more robust to noise than type-1 fuzzy sets. The recurrent structure in the RSEIT2FNN helps to remember the context information of a test frame. The RSEIT2FNN outputs are compared with a parameter threshold to determine whether it is a speech or nonspeech period. The HWEE-based RSEIT2FNN detection was applied to speech detection in different noisy environments with different noise levels. Comparisons with different detection methods verified the advantage of the proposed method of using HWEE.     

Computational organization of didactic contents for personalized virtual learning environments

This paper presents an organization model for personalized didactic contents used in individual study environments. For many students the availability of contents in a general form might not be effective. A multilevel structure of concepts is proposed to provide different presentation combinations of the same content. Our work shows that it is possible to personalize the didactic content in order to encourage students, by using proximal learning patterns. These patterns are obtained from the analysis of the actions of students with positive results in the individual content organization. The system uses artificial intelligence techniques to reactively organize and personalize content. Personalization is made possible by means of an artificial neural network that classifies the student's profile and assigns it a proximal learning pattern. Expert rules are used to mediate and adjust the contents reactively. Experimental results indicate that the approach is efficient and provides the student a better use of the content with adaptive and reactive personalized presentation.     

Nonlinear black-box models in system identification: Mathematical foundations

We discuss several aspects of the mathematical foundations of the nonlinear black-box identification problem. We shall see that the quality of the identification procedure is always a result of a certain trade-off between the expressive power of the model we try to identify (the larger the number of parameters used to describe the model, the more flexible is the approximation), and the stochastic error (which is proportional to the number of parameters). A consequence of this trade-off is the simple fact that a good approximation technique can be the basis of a good identification algorithm. From this point of view, we consider different approximation methods, and pay special attention to spatially adaptive approximants. We introduce wavelet and ‘neuron’ approximations, and show that they are spatially adaptive. Then we apply the acquired approximation experience to estimation problems. Finally, we consider some implications of these theoretical developments for the practically implemented versions of the ‘spatially adaptive’ algorithms.     

基于神经网络的一类大系统动态递阶优化方法

提出了一种用于求解离散时间大系统动态递阶优化问题的神经网络模型(LHONN),该网络以全集成化为特征:1)各子系统的动态方程嵌入相应的局部优化网络中,使得网络结构具有较低的维数,易于硬件实现;2)其上级协调网络和局部优化网络的求解过程同时进行,优化求解速度高,适宜于实时系统优化.     

Trust, control and the role of interorganizational systems in electronic partnerships

Abstract. To survive and thrive in today's competitive marketplace, organizations are increasingly migrating to new organizational structures in which partnerships and interorganizational systems (IOSs) are becoming more important. The success of these partnerships depends on both trust and control – complex constructs that act on and shape each other over time. Many organizations assume that high levels of trust are necessary for net-enabled electronic partnerships. We examine this assumption from two perspectives: the initial decision to enter into a partnership or alliance, and its ongoing operation. Our findings suggest that researchers have treated trust simplistically, failing to distinguish the need for trust (which is inversely related to the organization's ability to control its partners) and the level of trust (which is an actual quantity that may change during the lifetime of the partnership). In many organizations, there is a gap between these two trust dimensions, which management attempts to close by changing the level of control. In this process, the IOS is key. To understand the relationship of IOS use to trust and control, we applied structured content analysis and analytic induction to 16 published case studies and used the results to create a framework for relating trust and control. At the heart of the framework is the recognition that trust and control are not simple substitutes for each other. Rather, they form a dialectic, where it makes sense to consider each construct only in relationship to the other. Using the framework, we identify areas for follow-up research and suggestions for practitioners.     

A neural network based multi-classifier system for gene identification in DNA sequences

The paper presents a neural network based multi-classifier system for the identification of Escherichia coli promoter sequences in strings of DNA. As each gene in DNA is preceded by a promoter sequence, the successful location of an E. coli promoter leads to the identification of the corresponding E. coli gene in the DNA sequence. A set of 324 known E. coli promoters and a set of 429 known non-promoter sequences were encoded using four different encoding methods. The encoded sequences were then used to train four different neural networks. The classification results of the four individual neural networks were then combined through an aggregation function, which used a variation of the logarithmic opinion pool method. The weights of this function were determined by a genetic algorithm. The multi-classifier system was then tested on 159 known promoter sequences and 171 non-promoter sequences not contained in the training set. The results obtained through this study proved that the same data set, when presented to neural networks in different forms, can provide slightly varying results. It also proves that when different opinions of more classifiers on the same input data are integrated within a multi-classifier system, we can obtain results that are better than the individual performances of the neural networks. The performances of our multi-classifier system outperform the results of other prediction systems for E. coli promoters developed so far.

Institution-based trust in interorganizational exchange relationships: the role of online B2B marketplaces on trust formation

Given the uncertainty of online transactions, the digital economy encourages the creation of institutional structures that assure online interorganizational exchange relationships. This research examines how institution-based trust develops in online B2B marketplaces to facilitate interorganizational trust (buyers' trust in sellers). Building upon the notion of institutional trust [Zucker,1986], this study proposes how specific institution-based structures help engender interorganizational trust and indirectly influence transaction success in B2B marketplaces. Five specific institution-based mechanisms are proposed—perceived monitoring, perceived legal bonds, perceived accreditation, perceived feedback, and perceived cooperative norms. To assess the influence of the proposed two dimensions of interorganizational trust—credibility and benevolence—in buyer–seller relationships, three trust outcomes are examined—satisfaction, perceived risk, and continuity. The proposed model is tested on data from 102 organizational buyers in an online B2B marketplace. The results support the proposed model, delineating the relationship between institution-based trust and interorganizational trust. The study provides evidence on how specific institutional mechanisms build trust in online B2B marketplaces, stressing the ability of institution-based trust to build a trustworthy trading environment in the digital economy. The paper discusses the theoretical and managerial implications of this study and proposes several suggestions for future research.     

Selection of input variables for model identification of static nonlinear systems

System identification can be divided into structure and parameter identification. In most system-identification approaches the structure is presumed and only a parameter identification is performed to obtain the coefficients in the functional system. Yet, often there is little knowledge about the system structure. In such cases, the first step has to be the identification of the decisive input variables. In this paper a black-box input variable identification approach using feedforward neural networks is proposed.