Co-evolution of Information Systems in Fast-Growing Small Firms

The paper examines the co-evolution of different dimensions of information systems for a sample of fast-growing small firms. The investigation uses primary source longitudinal empirical evidence. The data are taken from a large database on the lifecycle experience of one-hundred-and-fifty new business starts over a four-year period. They were collected by face to face interviews with owner-managers of small entrepreneurial firms. Interviews were conducted using an administered questionnaire that covered the agenda of markets, finance, costs, business strategy, the development of a management information system, human capital, organisation and technical change. This work uses primarily the data on management information systems. The basic approach used is to compare the attributes of the fastest and slowest paced firms, as identified by their growth rates. We then examine the evolution of these firms' management information systems. The measures used to identify changes in systems include: capital investment techniques, such as return on investment, residual income, net present value, internal rate of return and payback period; methods for managing costs, like just-in-time management, activity-based costing, quantitative risk analysis, value analysis, strategic pricing and transfer pricing; and using computer applications for storing information, project appraisal, financial modelling, forecasting and sensitivity analysis. 'Time lines' are graphed to show the points at which various features of information systems are introduced (e.g. data storage, forecasting, sensitivity analysis), and derived techniques (e.g. ROI, ABC) implemented. Firms are dichotomised into highgrowth and low-growth groups. Comparisons are made within firms and across firms in terms of the co-evolution of different aspects of their accounting information systems

Social media analytics: a survey of techniques, tools and platforms

This paper is written for (social science) researchers seeking to analyze the wealth of social media now available. It presents a comprehensive review of software tools for social networking media, wikis, really simple syndication feeds, blogs, newsgroups, chat and news feeds. For completeness, it also includes introductions to social media scraping, storage, data cleaning and sentiment analysis. Although principally a review, the paper also provides a methodology and a critique of social media tools. Analyzing social media, in particular Twitter feeds for sentiment analysis, has become a major research and business activity due to the availability of web-based application programming interfaces (APIs) provided by Twitter, Facebook and News services. This has led to an ‘explosion’ of data services, software tools for scraping and analysis and social media analytics platforms. It is also a research area undergoing rapid change and evolution due to commercial pressures and the potential for using social media data for computational (social science) research. Using a simple taxonomy, this paper provides a review of leading software tools and how to use them to scrape, cleanse and analyze the spectrum of social media. In addition, it discussed the requirement of an experimental computational environment for social media research and presents as an illustration the system architecture of a social media (analytics) platform built by University College London. The principal contribution of this paper is to provide an overview (including code fragments) for scientists seeking to utilize social media scraping and analytics either in their research or business. The data retrieval techniques that are presented in this paper are valid at the time of writing this paper (June 2014), but they are subject to change since social media data scraping APIs are rapidly changing

Reformulating software engineering as a search problem

Metaheuristic techniques such as genetic algorithms, simulated annealing and tabu search have found wide application in most areas of engineering. These techniques have also been applied in business, financial and economic modelling. Metaheuristics have been applied to three areas of software engineering: test data generation, module clustering and cost/effort prediction, yet there remain many software engineering problems which have yet to be tackled using metaheuristics. It is surprising that metaheuristics have not been more widely applied to software engineering; many problems in software engineering are characterised by precisely the features which make metaheuristics search applicable. In the paper it is argued that the features which make metaheuristics applicable for engineering and business applications outside software engineering also suggest that there is great potential for the exploitation of metaheuristics within software engineering. The paper briefly reviews the principal metaheuristic search techniques and surveys existing work on the application of metaheuristics to the three software engineering areas of test data generation, module clustering and cost/effort prediction. It also shows how metaheuristic search techniques can be applied to three additional areas of software engineering: maintenance/evolution system integration and requirements scheduling. The software engineering problem areas considered thus span the range of the software development process, from initial planning, cost estimation and requirements analysis through to integration, maintenance and evolution of legacy systems. The aim is to justify the claim that many problems in software engineering can be reformulated as search problems, to which metaheuristic techniques can be applied. The goal of the paper is to stimulate greater interest in metaheuristic search as a tool of optimisation of software engineering problems and to encourage the investigation and exploitation of these technologies in finding near optimal solutions to the complex constraint-based scenarios which arise so frequently in software engineering

THE INTERNATIONALIZATION OF SMES. A SYNTHETIC ANALYSIS OF THE DECISIONAL FACTORS AND PROCESS

Having an increased complexity, the internationalization process of small and medium- sized enterprises (SMEs) becomes, in the context of globalization and of the freedom of circulation of goods, services, and capital, a decisive factor of both the evolution of the company and the economic force distribution report on the market. The evolution of the world economic system opened a wide action field for small and medium sized companies, who had to adapt to new rules. The internationalization of SMEs is no longer an option, but it becomes a condition of their existence. A high importance in this process belongs to the way decisions are made, both regarding the target market and the entry option, the way entry barriers are overcome and the promotional techniques in this extended business environment. A synthetic analysis of the decisional factors and process is needed in order to fully and correctly understand the internationalization strategies adopted by SMEs. This paper is built around three major objectives, with the scope of determining the SMEs’ internationalization decisions, as well s the impediments met in the process. The paper contributes to the literature in the field of the internationalization of SMEs through the analysis and interpretation of the results acquired during the study regarding their behavior towards the activity expansion on international markets

DOES ENTERPRISE ARCHITECTURE SUPPORT THE DIGITAL TRANSFORMATION ENDEAVORS? QUESTIONING THE OLD CONCEPTS IN LIGHT OF NEW FINDINGS

Digital transformation commonly refers to a disruptive process that changes significally the way organizations evolve, compete, interact and create value. Therefore, it is critical for companies to hadle with the business potential of innovative digital capabilities, to update their operational and decision making processes and to develop new strategic business models. In this complex endeavor, the evolution of firm’s information system is an important facet that brings together technology, organization and human actors. Enterprise Architecture (EA) methods and frameworks are proposed as essential techniques to handle such evolutions. However, the complex and disruptive nature of the underlying transformations raise multiple questions concerning the adequacy of EA for digital transformation projects. Therefore, this paper aims to examine the extent to which existing EA approaches support such projects. It presents an analysis of interviews with both IT and business projects managers from five different companies. We asked about concrete projects, both about the project goals and the EA methods used, but also about the difficulties and challenges they face in their daily work when using EA frameworks. The analysis show that although existing EA frameworks are essential tools to sup-port and drive digital transformation projects, some important contextual and organizational characteristics are missing. These characteristics are discussed and a research agenda is suggested to fill this gap

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences

To ensure sustainable software maintenance and evolution, a diverse set of activities and concepts like metrics, change impact analysis, or antipattern detection can be used. Special maintainability assurance techniques have been proposed for service- and microservice-based systems, but it is difficult to get a comprehensive overview of this publication landscape. We therefore conducted a systematic literature review (SLR) to collect and categorize maintainability assurance approaches for service-oriented architecture (SOA) and microservices. Our search strategy led to the selection of 223 primary studies from 2007 to 2018 which we categorized with a threefold taxonomy: a) architectural (SOA, microservices, both), b) methodical (method or contribution of the study), and c) thematic (maintainability assurance subfield). We discuss the distribution among these categories and present different research directions as well as exemplary studies per thematic category. The primary finding of our SLR is that, while very few approaches have been suggested for microservices so far (24 of 223, ?11%), we identified several thematic categories where existing SOA techniques could be adapted for the maintainability assurance of microservices

On the role of Prognostics and Health Management in advanced maintenance systems

The advanced use of the Information and Communication Technologies is evolving the way that systems are managed and maintained. A great number of techniques and methods have emerged in the light of these advances allowing to have an accurate and knowledge about the systems’ condition evolution and remaining useful life. The advances are recognized as outcomes of an innovative discipline, nowadays discussed under the term of Prognostics and Health Management (PHM). In order to analyze how maintenance will change by using PHM, a conceptual model is proposed built upon three views. The model highlights: (i) how PHM may impact the definition of maintenance policies; (ii) how PHM fits within the Condition Based Maintenance (CBM) and (iii) how PHM can be integrated into Reliability Centered Maintenance (RCM) programs. The conceptual model is the research finding of this review note and helps to discuss the role of PHM in advanced maintenance systems.EU Framework Programme Horizon 2020, 645733 - Sustain-Owner - H2020-MSCA-RISE-201

Global perspectives on legacy systems

Summarises findings of two international workshops on legacy systems, held in conjunction with an EPSRC managed programme. Issues covered include the nature and dynamics of legacy systems, the co-evolution of software and organisations, issues around software as a technology (its engineering and its management), and organisational/people issues

Strategic marketing planning : a state of the art review

School of Managemen