Culture in global business transformation projects : the discovery of a grounded theory

Presently organisations engage in what is termed as Global Business Transformation Projects [GBTPs], for consolidating, innovating, transforming and restructuring their processes and business strategies while undergoing fundamental change. Culture plays an important role in global business transformation projects as these involve people of different cultural backgrounds and span across countries, industries and disciplinary boundaries. Nevertheless, there is scant empirical research on how culture is conceptualised beyond national and organisational cultures but also on how culture is to be taken into account and dealt with within global business transformation projects. This research is situated in a business context and discovers a theory that aids in describing and dealing with culture. It draws on the lived experiences of thirty-two senior management practitioners, reporting on more than sixty-one global business transformation projects in which they were actively involved. The research method used is a qualitative and interpretive one and applies a grounded theory approach, with rich data generated through interviews. In addition, vignettes were developed to illustrate the derived theoretical models. The findings from this study contribute to knowledge in multiple ways. First, it provides a holistic account of global business transformation projects that describe the construct of culture by the elements of culture types, cultural differences and cultural diversity. A typology of culture types has been developed which enlarges the view of culture beyond national and organisational culture including an industry culture, professional service firm culture and 'theme' culture. The amalgamation of the culture types instantiated in a global business transformation project compromises its project culture. Second, the empirically grounded process for managing culture in global business transformation projects integrates the stages of recognition, understanding and management as well as the enablement providing a roadmap for dealing with culture in global business transformation projects. Third, this study identified contextual variables to global business transformation projects, which provide the means of describing the environment global business transformation projects are situated, influence the construct of culture and inform the process for managing culture. Fourth, the contribution to the research method is the positioning of interview research as a strategy for data generation and the detailed documentation applying grounded theory to discover theory.

A data mining based method for discovery of web services and their compositions

Due to the availability of huge number of web services, finding an appropriate Web service according to the requirements of a service consumer is still a challenge. Moreover, sometimes a single web service is unable to fully satisfy the requirements of the service consumer. In such cases, combinations of multiple inter-related web services can be utilised. This paper proposes a method that first utilises a semantic kernel model to find related services and then models these related Web services as nodes of a graph. An all-pair shortest-path algorithm is applied to find the best compositions of Web services that are semantically related to the service consumer requirement. The recommendation of individual and composite Web services composition for a service request is finally made. Empirical evaluation confirms that the proposed method significantly improves the accuracy of service discovery in comparison to traditional keyword-based discovery methods.

Recreational needs and service performance expectations

The theoretical contribution of this study lies with its focus on subjective experiencing, that is, the emotional convergence between feeling states, and perceptions of servicescapes and holiday activities. An empirical study models the impact of recreational needs on the perceived importance of destination attributes and intentions to participate in activities. A sample of prospective tourists was asked to indicate how important they considered servicescape elements to be in their general holiday planning. They were also asked to report on their emotional state (orientation) as a proxy for their needs for recreation, and to state their intention and likely involvement with holiday activities. Results suggest that those with high recreational needs (self-reflexive and inward-looking) regard elements of tourism servicescapes as significantly more important than those without (who are outward-looking and energetic), as well as show significant variations in their inclinations to be active and explorative at destinations. Rather, those with higher recreational needs as measured by combinations of lack of energy, self-confidence, and physiological well-being look for creature comfort, coziness, and familiarity, in other words, for things they already know and have experienced before. Subjective experiencing and service performance evaluations are thereby suggested to be influenced by emotional states. These states may also impact tourists' recognition of destination uniqueness as a major component of a destination's competitive advantage that cannot easily be copied. As a consequence, it may be worth reconsidering the role of recreation in tourism service design. Turning an inwardlooking focus bent on recreation to an outward-looking one interested in discovery would enable more tourists to more fully experience the destination before they leave.

Refactoring Service Interface to Support Artefact-centric Service interaction

The growth of APIs and Web services on the Internet, especially through larger enterprise systems increasingly being leveraged for Cloud and software-as-a-service opportunities, poses challenges for improving the efficiency of integration with these services. Interfaces of enterprise systems are typically larger, more complex and overloaded, with single operations having multiple data entities and parameter sets, supporting varying requests, and reflecting versioning across different system releases, compared to fine-grained operations of contemporary interfaces. We propose a technique to support the refactoring of service interfaces by deriving business entities and their relationships. In this paper, we focus on the behavioural aspects of service interfaces, aiming to discover the sequential dependencies of operations (otherwise known as protocol extraction) based on the entities and relationships derived. Specifically, we propose heuristics according to these relationships, and in turn, deriving permissible orders in which operations are invoked. As a result of this, service operations can be refactored on business entity CRUD lines, with explicit behavioural protocols as part of an interface definition. This supports flexible service discovery, composition and integration. A prototypical implementation and analysis of existing Web services, including those of commercial logistic systems (Fedex), are used to validate the algorithms proposed through the paper.

Distributed Robotic Vision as a service

The vision sense of standalone robots is limited by line of sight and onboard camera capabilities, but processing video from remote cameras puts a high computational burden on robots. This paper describes the Distributed Robotic Vision Service, DRVS, which implements an on-demand distributed visual object detection service. Robots specify visual information requirements in terms of regions of interest and object detection algorithms. DRVS dynamically distributes the object detection computation to remote vision systems with processing capabilities, and the robots receive high-level object detection information. DRVS relieves robots of managing sensor discovery and reduces data transmission compared to image sharing models of distributed vision. Navigating a sensorless robot from remote vision systems is demonstrated in simulation as a proof of concept.

A Distributed Robotic Vision Service

Robotic vision is limited by line of sight and onboard camera capabilities. Robots can acquire video or images from remote cameras, but processing additional data has a computational burden. This paper applies the Distributed Robotic Vision Service, DRVS, to robot path planning using data outside line-of-sight of the robot. DRVS implements a distributed visual object detection service to distributes the computation to remote camera nodes with processing capabilities. Robots request task-specific object detection from DRVS by specifying a geographic region of interest and object type. The remote camera nodes perform the visual processing and send the high-level object information to the robot. Additionally, DRVS relieves robots of sensor discovery by dynamically distributing object detection requests to remote camera nodes. Tested over two different indoor path planning tasks DRVS showed dramatic reduction in mobile robot compute load and wireless network utilization.

A literary occupation: responses of German writers in service in occupied Europe

This thesis examines the literary output of German servicemen writers writing from the occupied territories of Europe in the period 1940-1944. Whereas literary-biographical studies and appraisals of the more significant individual writers have been written, and also a collective assessment of the Eastern front writers, this thesis addresses in addition the German literary responses in France and Greece, as being then theatres of particular cultural/ideological attention. Original papers of the writer Felix Hartlaub were consulted by the author at the Deutsches Literatur Archiv (DLA) at Marbach. Original imprints of the wartime works of the subject writers are referred to throughout, and citations are from these. As all the published works were written under conditions of wartime censorship and, even where unpublished, for fear of discovery written in oblique terms, the texts were here examined for subliminal authorial intention. The critical focus of the thesis is on literary quality: on aesthetic niveau, on applied literary form, and on integrity of authorial intention. The thesis sought to discover: (1) the extent of the literary output in book-length forms. (2) the auspices and conditions under which this literary output was produced. (3) the publication history and critical reception of the output. The thesis took into account, inter alia: (1) occupation policy as it pertained locally to the writers’ remit; (2) the ethical implications of this for the writers; (3) the writers’ literary stratagems for negotiating the constraints of censorship.

Women's help seeking behaviour and the associated influencing factors on self discovery of a breast symptom

To investigate women’s help seeking behavior (HSB) following self discovery of a breast symptom and determine the associated influencing factors. A descriptive correlation design was used to ascertain the help seeking behavior (HSB) and the associated influencing factors of a sample of women (n = 449) with self discovered breast symptoms. The study was guided by the ‘Help Seeking Behaviour and Influencing Factors” conceptual framework (Facione et al., 2002; Meechan et al., 2003, 2002; Leventhal, Brissette and Leventhal, 2003 and O’Mahony and Hegarty, 2009b). Data was collected using a researcher developed multi-scale questionnaire package to ascertain women’s help seeking behavior on self discovery of a breast symptom and determine the factors most associated with HSB. Factors examined include: socio-demographics, knowledge and beliefs (regarding breast symptom; breast changes associated with breast cancer; use of alternative help seeking behaviours and presence or absence of a family history of breast cancer),emotional responses, social factors, health seeking habits and health service system utilization and help seeking behavior. A convenience sample (n = 449 was obtained by the researcher from amongst women attending the breast clinics of two large urban hospitals within the Republic of Ireland. All participants had self-discovered breast symptoms and no previous history of breast cancer. The study identified that while the majority of women (69.9%; n=314) sought help within one month, 30.1% (n=135) delayed help seeking for more than one month following self discovery of their breast symptom. The factors most significantly associated with HSB were the presenting symptom of ‘nipple indrawn/changes’ (p = 0.005), ‘ignoring the symptom and hoping it would go away’ (p < 0.001), the emotional response of being ‘afraid@ on symptom discovery (p = 0.005) and the perception/belief in longer symptom duration (p = 0.023). It was found that women who presented with an indrawn/changed nipple were more likely to delay (OR = 4.81) as were women who ‘ignored the symptoms and hoped it would go away’ (OR = 10.717). Additionally, the longer women perceived that their symptom would last, they more likely they were to delay (OR = 1.18). Conversely, being afraid following symptom discovery was associated with less delay (OR = 0.37; p=0.005). This study provides further insight into the HSB of women who self discovered breast symptoms. It highlights the complexity of the help seeking process, indicating that is not a linear event but is influenced by multiple factors which can have a significant impact on the outcomes in terms of whether women delay or seek help promptly. The study further demonstrates that delayed HSB persists amongst women with self discovered breast symptoms. This has important implications for continued emphasis on the promotion of breast awareness, prompt help seeking for self discovered breast symptoms and early detection and treatment of breast cancer, amongst women of all ages.

Delivering mobile cloud services to the user: description, discovery, and consumption

The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Putting meaning into NETMAR – the open service network for marine environmental data

The open service network for marine environmental data (NETMAR) project uses semantic web technologies in its pilot system which aims to allow users to search, download and integrate satellite, in situ and model data from open ocean and coastal areas. The semantic web is an extension of the fundamental ideas of the World Wide Web, building a web of data through annotation of metadata and data with hyperlinked resources. Within the framework of the NETMAR project, an interconnected semantic web resource was developed to aid in data and web service discovery and to validate Open Geospatial Consortium Web Processing Service orchestration. A second semantic resource was developed to support interoperability of coastal web atlases across jurisdictional boundaries. This paper outlines the approach taken to producing the resource registry used within the NETMAR project and demonstrates the use of these semantic resources to support user interactions with systems. Such interconnected semantic resources allow the increased ability to share and disseminate data through the facilitation of interoperability between data providers. The formal representation of geospatial knowledge to advance geospatial interoperability is a growing research area. Tools and methods such as those outlined in this paper have the potential to support these efforts.

WAIS seminar: Application Performance Monitoring and Architecture Discovery with Kieker

Wednesday 23rd April 2014 Speaker(s): Willi Hasselbring Organiser: Leslie Carr Time: 23/04/2014 14:00-15:00 Location: B32/3077 File size: 802Mb Abstract The internal behavior of large-scale software systems cannot be determined on the basis of static (e.g., source code) analysis alone. Kieker provides complementary dynamic analysis capabilities, i.e., monitoring/profiling and analyzing a software system's runtime behavior. Application Performance Monitoring is concerned with continuously observing a software system's performance-specific runtime behavior, including analyses like assessing service level compliance or detecting and diagnosing performance problems. Architecture Discovery is concerned with extracting architectural information from an existing software system, including both structural and behavioral aspects like identifying architectural entities (e.g., components and classes) and their interactions (e.g., local or remote procedure calls). In addition to the Architecture Discovery of Java systems, Kieker supports Architecture Discovery for other platforms, including legacy systems, for instance, inplemented in C#, C++, Visual Basic 6, COBOL or Perl. Thanks to Kieker's extensible architecture it is easy to implement and use custom extensions and plugins. Kieker was designed for continuous monitoring in production systems inducing only a very low overhead, which has been evaluated in extensive benchmark experiments. Please, refer to http://kieker-monitoring.net/ for more information.

Collaborative personal profiling for web service ranking and recommendation

Web service is one of the most fundamental technologies in implementing service oriented architecture (SOA) based applications. One essential challenge related to web service is to find suitable candidates with regard to web service consumer’s requests, which is normally called web service discovery. During a web service discovery protocol, it is expected that the consumer will find it hard to distinguish which ones are more suitable in the retrieval set, thereby making selection of web services a critical task. In this paper, inspired by the idea that the service composition pattern is significant hint for service selection, a personal profiling mechanism is proposed to improve ranking and recommendation performance. Since service selection is highly dependent on the composition process, personal knowledge is accumulated from previous service composition process and shared via collaborative filtering where a set of users with similar interest will be firstly identified. Afterwards a web service re-ranking mechanism is employed for personalised recommendation. Experimental studies are conduced and analysed to demonstrate the promising potential of this research.

Performance Analysis of a Semantics Enabled Service Registry

Service discovery is a critical task in service-oriented architectures such as the Grid and Web Services. In this paper, we study a semantics enabled service registry, GRIMOIRES, from a performance perspective. GRIMOIRES is designed to be the registry for myGrid and the OMII software distribution. We study the scalability of GRIMOIRES against the amount of information that has been published into it. The methodology we use and the data we present are helpful for researchers to understand the performance characteristics of the registry and, more generally, of semantics enabled service discovery. Based on this experimentation, we claim that GRIMOIRES is an efficient semantics-aware service discovery engine.

Performance Analysis of a Semantics Enabled Service Registry

Service discovery is a critical task in service-oriented architectures such as the Grid and Web Services. In this paper, we study a semantics enabled service registry, GRIMOIRES, from a performance perspective. GRIMOIRES is designed to be the registry for myGrid and the OMII software distribution. We study the scalability of GRIMOIRES against the amount of information that has been published into it. The methodology we use and the data we present are helpful for researchers to understand the performance characteristics of the registry and, more generally, of semantics enabled service discovery. Based on this experimentation, we claim that GRIMOIRES is an efficient semantics-aware service discovery engine.