Aneesh Zutshi

The Business Interoperability Quotient Measurement Model

Over the last decade, the context of interoperability has been changing rapidly. It has been expanding from the largely technically focused area of Information Systems toward Business Processes and Business Semantics. However, there exists a need for established methods to define Business Interoperability and provide for measuring its performance as a first step toward improving interoperability conditions between collaborating entities. This paper proposes a model that captures the factors that are responsible for Business Interoperability in the context of collaborative business processes. The Business Interoperability Quotient Measurement Model (BIQMM) uses an interdisciplinary approach to embrace the key elements responsible for collaboration performance. Through the quantification of the importance of each element to the particular collaboration scenario, and by combining the BIQMM with the Analytical Network Process (ANP) approach, this model enables a quantitative analysis of Business Interoperability, so that an overall interoperability score can be calculated for enhanced performance measurements. Two application scenarios are presented, validating the proposed model.

A Dynamic Agent-Based Modeling Framework for Digital Business Models: Applications to Facebook and a Popular Portuguese Online Classifieds Website

This paper presents an Agent Based Modeling Framework that can be used to model any internet based business. The model captures the unique characteristics that define how online users interact, share information, and take product adoption decisions. This model can be used to simulate business performance, make business forecasts, and test business strategies. To demonstrate the model, we have applied it to Facebook as well as a leading Portuguese online classifieds website – CustoJusto.pt. Through a number of cases, we have simulated the growth forecasts, its impact by changes in pricing, and changes in the Business Model itself.

A Vector Space Model Approach for Searching and Matching Product E-Catalogues

In e-procurement, companies use e-catalogues to exchange product information with business partners. The large variety of e-catalogue formats which are used by various companies make it difficult to match a product request from a buyer (buyer e-catalogue) with products e-catalogues. While, there are too many different standards for e-catalogues in use, often companies do not follow standard formats. Hence we often encounter a plethora of catalogue formats ranging from unstructured text to well-structured XML documents. One traditional approach to solve this problem is to convert different formats to a general common structure. But within this heterogeneous set of known or even unknown structures achieving a global structure is impractical. In this paper, vector space model has been used to measure the similarity ratio of providers’ e-catalogues with a buyer’s e-catalogue. Attributes of known structures and their values have been used as terms and their weights in the vectors to find the correlation of e-catalogues based on relationship of common tags. In order to associate the structures in calculating similarity, levels of attributes in xml documents are also included in the terms. Natural language processing is used to extract the same attributes from unstructured or unknown structured documents.

ICIF: an inter-cloud interoperability framework for computing resource cloud providers in factories of the future

Factories of the future (FoF) is a relatively new topic focusing on developing competitive manufacturing. Exploiting cloud services is a vital area for FoF. The collaboration between different cloud vendors can provide better quality of service at a lower price. This paper discusses a framework which supports inter-cloud interoperability in a heterogeneous computing resource cloud environment with the goal of dispatching the workload to the most effective clouds available at runtime. Moreover, a genetic algorithm (GA)–based job-scheduler is proposed as a part of the interoperability framework offering workload migration with the best performance at the least cost. The resource selection model is evaluated using agent-based simulation approach.

Matching heterogeneous e-catalogues in B2B marketplaces using vector space model

Competitive pressures require manufacturers to continually find ways to reduce costs and increase market access. Internet-based technologies such as e-procurement (electronic procurement) provide increased buying and selling opportunities to manufacturers. E-catalogues are electronic representations of information about the products and services of an enterprise and play a key role in e-procurement. Matching an e-catalogue from a buyer with product e-catalogues provided by the suppliers helps companies to find partners in e-marketplaces. Since each business actor may use a different structure and classification for e-catalogues, it is not easy to match a product with the e-catalogue requested by another partner. This article uses vector space model (VSM) and customises it to solve the matching problem of the e-catalogues. The proposed approach uses a combinations of values, names and location of attributes of structured documents to find the syntactic correlation of e-catalogues. It also uses ontologies to expand the matching mechanism with semantic relationships of data attributes. The proposed approach makes it possible to use the benefits of all available ontologies and schemas but not to be dependent on them. The experimental results show that the proposed approach provides a more accurate similarity ratio while matching similar e-catalogues compared with the basic approach of just using VSM.

Semantic and syntactic matching of e-catalogues: Using Vector Space Model

E-catalogues play a key role in e-procurement. Matching a product request from a buyer with products e-catalogues, helps companies to find business partners in e-marketplaces. Plethora of e-catalogue standards and enterprise specific formats is one of the major challenges in the matching process. In addition to this syntactic heterogeneity, the same product concept can be expressed using different words that causes semantic diversity in e-catalogues. In this paper, we propose a flexible approach to e-catalogue matching using Vector Space Model. Each e-catalogue is interpreted syntactically in its schema and semantically in an ontology that is developed based on its product classification system. Schemas and ontologies are added to the VSM by adding the syntax of the structure and semantic of the ontology to the indexing and searching mechanisms. The matching process uses the syntactic and semantic metadata for interpreting each e-catalogue as much as the information is available for the system, but is not dependent on this information.

DYNAMOD—An Agent Based Modeling Framework: Applications to Online Social Networks

This paper presents an Agent Based Modeling Framework that seeks to provide a generic model that can be used to simulate any internet based business. The model captures the unique characteristics that define how online users interact, share information, and take product adoption decisions. This model can be used to simulate business performance, make business forecasts, and test business strategies. To demonstrate the applicability of the model, we choose two social networks with opposing scales: Facebook and a startup educational social network—weduc.pt.

DYNAMOD: A Modelling Framework for Digital Businesses based on Agent Based Modeling

This paper introduces a Dynamic Agent Based Modelling Framework (DYNAMOD) that is designed for developing Digital Business Simulations. The model is based on literature review of three complementary research areas: Business Models, Business Applications of Agent Based Modeling and Digital Business Characteristics. This Framework is customisable and computationally implements key digital business characteristics including network effects, online and offline word of mouth, pricing strategies, amongst other features of the Digital Business Environment. DYNAMOD can be a generic framework for developing a variety of forcasting and simulation models that can provide a new computational approach to Digital Business Modeling and Analysis.

A Conceptual Framework of Risk Treatment in Scale up Companies Supported by Using Nudge Theory

This article analyzes the potential benefits of applying Nudge Theory for risk management in scaling up companies. Considering importance of risk management in preventing failure of firms to entrepreneurs; this research uses the notion of Behavioural Economics to offer valuable insights into how scaling up companies can benefit from the implementation of risk management process supported by applying nudges techniques. To overcome some of the barriers in implementing the risk management; we propose a conceptual framework for risk mitigation, which is based on Nudge theory and using behavioral approach. The goal is to contribute to the success of scale up companies during transition period by improving the efficiency of risk treatment. This study seeks to take an essential step towards a general understanding of the influence of utilizing Nudging for employees in planning of risk actions. This paper reviews some challenges of implementing Enterprise Risk Management (ERM). We focus on behavioural solutions in risk treatment to overcome a part of the barriers. Additionally, the concept of “Nudg” and some nudge techniques are explained that are used in the presented framework. We conclude by outlining relevant ideas for further investigation on this topic, by suggesting a set of implications for academics and policymakers.

Simulation and forecasting of digital pricing models for an e-procurement platform using an agent-based simulation model

Online businesses can be represented as a complex interaction of interconnected online users responding to the value proposition of an online company. We propose a Dynamic Agent-Based Modeling framework (DYNAMOD) that aims to explain these complex dynamics. This framework aids in the creation of simulation models that mimic the actual market behavior and perform business forecasting and decision support functions. Through a case study of the largest e-procurement provider in Portugal – Vortal.biz, we simulate their pricing model and analyze revenue impact by optimizing pricing using genetic algorithms. The objective of this research is to propose agent-based model as an effective method to forecast the impact of pricing decisions.