Knowledge retrieval for configuring risks when answering calls to tenders or direct customer demands

This short article provides the first ideas and results about the configuration of risks when answering tenders or direct customer demands. Indeed, when an offer is defined, it becomes more and more important to analyze possibilities of risks occurrence and their consequences. Most of the time, this analysis is conducted manually thanks to a risk expert. In this paper, we propose to assist the expert with a risk configuration tool that relies on a knowledge base and that allows to define and evaluate: (i) the risk probability, (ii) the main risk impacts and (iii) the interests of various corrective and preventive actions to mitigate it. We first detail the problem. Then we propose a generic model of risks for calls for tenders. Then we describe some knowledge retrieval queries that support the configuration of risk characteristics. As preliminary studies, we will not be able to discuss hard theoretical results but should be able to show a nice a demo of a first software prototype.Outils logiciels et ProcEssus pour la Réponse à Appel d'Offre

Organisational routines in project-based organisations: an exploratory study

This research explores the existence and evolution of organizational routines in small firm Project-Based Organisations (PBOs). To reach this aim, it investigates the interplay between the two aspects making up a routine: ostensive – i.e. the abstract representation – and performative – i.e. actual implementation. PBOs represent an interesting context, because project differences and discontinuities challenge the emergence, development and evolution of routines, yet the requirements of efficiency and co-ordination through repeated, similar actions would suggest the need for routines even in small firm PBOs. I have adopted an inductive case study research. The empirical setting is a Public Relation and Communication agency, where small firm PBOs are a typical form of organisation. The process nature of the subject of inquiry required a combination of bottom up and top down approaches that enabled me to identify and analyse routines in depth. As per the topdown approach, relying on extant theory, I developed a list of concepts discussed in the literature on organisational routines that in turn provided the basis for a framework within which analyse the empirical evidence. The bottom up approach draws on descriptive narratives, visual mapping, and grounded theory. The research provides both theoretical and empirical contributions towards a better understanding of the characteristics and evolution of organisational routines in small firm PBOs. Routines exist and are important for coordination and efficiency even in small firm PBOs. They are project procedures not necessarily embedded in any artefact, but perceived as regular processes by project participants. Across projects routines evolve by adapting to the context where they take place. Contexts are in turn shaped by contingencies pertaining to the actors, the project, organisational departments, and the specificities of the customer and the markets they serve. These contingencies define problems and issues that actors involved in the routine face. Facing problems and issues causes the routine to adapt, making the sequence and the content of the actions forming it different across projects. Predictability and recurrence of contingencies and related issues determine how routines adaptation occurs. When contingencies and issues are expected and recur across several projects, adaptation is planned in advance and is supposed to concern both ostensive and performative aspects of the routine. When contingencies and issues are less predictable or occur in just a single project, adaptation concerns only the performative aspect, keeping unchanged the ostensive one. In line with the low level of codification that informs small firm PBO activities, routines’ adaptation is not necessarily embedded in any artefact. However, when adaptation is imposed by the owner or senior management, it can be communicated clearly to the interested actors. For small firm PBOs, the research suggests that adaptation of the routines they implement is fundamental to carrying out project activities effectively. It also implies that when aiming to change the way the organisation operates, entrepreneurs and managers should pay attention to both to the design of the routines themselves and the way actors perceive and implement changes to the routines. In addition, the study suggests that further investigation on how firm size and sector shapes the characteristics and dynamics of routines would be invaluable to the field. Regarding theory, the thesis contributes an articulation of the relationship between the two aspects of routines, performative and ostensive. Further research on the nature and functioning of routines in other types of organisation and sector would address the limitations of extant literature and achieve a more comprehensive understanding of routines

An ebd-enabled design knowledge acquisition framework

Having enough knowledge and keeping it up to date enables designers to execute the design assignment effectively and gives them a competitive advantage in the design profession. Knowledge elicitation or acquisition is a crucial component of system design, particularly for tasks requiring transdisciplinary or multidisciplinary cooperation. In system design, extracting domain-specific information is exceedingly tricky for designers. This thesis presents three works that attempt to bridge the gap between designers and domain expertise. First, a systematic literature review on data-driven demand elicitation is given using the Environment-based Design (EBD) approach. This review address two research objectives: (i) to investigate the present state of computer-aided requirement knowledge elicitation in the domains of engineering; (ii) to integrate EBD methodology into the conventional literature review framework by providing a well-structured research question generation methodology. The second study describes a data-driven interview transcript analysis strategy that employs EBD environment analysis, unsupervised machine learning, and a range of natural language processing (NLP) approaches to assist designers and qualitative researchers in extracting needs when domain expertise is lacking. The second research proposes a transfer-learning method-based qualitative text analysis framework that aids researchers in extracting valuable knowledge from interview data for healthcare promotion decision-making. The third work is an EBD-enabled design lexical knowledge acquisition framework that automatically constructs a semantic network -- RomNet from an extensive collection of abstracts from engineering publications. Applying RomNet can improve the design information retrieval quality and communication between each party involved in a design project. To conclude, this thesis integrates artificial intelligence techniques, such as Natural Language Processing (NLP) methods, Machine Learning techniques, and rule-based systems to build a knowledge acquisition framework that supports manual, semi-automatic, and automatic extraction of design knowledge from different types of the textual data source

The impact of enterprise information management capability on sustainable competitive advantage

In today’s economic environment, intense competition in the corporate world has prompted organizations to focus on creating and maintaining a sustainable competitive advantage (SCA). The purpose of this study is to explore the impact of enterprise information management capability (EIMC) on SCA. This study focuses on EIMC as An essential organizational dynamic capability and empirically examines the relationship between EIMC and SCA, both directly and indirectly, via two mediators: knowledge management (KM) and total quality management (TQM). This study used the theory of dynamic capability (DC) as the theoretical framework. Four constructs (EIMC, KM, TQM, and SCA) were developed and nine research hypotheses were examined. A mixed methods research design was used to collect primary data. The data was collected from twelve (12) semi-structured interviews with twelve (12) decision-makers from different organizations in the UAE. In addition, an online cross-sectional survey produced 144 responses from middle-level managers in UAE organizations. The survey data was analyzed using a partial least squares (PLS) approach to structural equation modeling. The results of the PLS measurement model suggest that the items used to measure the constructs were valid and reliable, and the results of the structural equation model supported every one of the research hypotheses. Moreover, the qualitative interviews’ data also supported every one of the research hypotheses. Therefore, the study results suggest that EIMC impacts positively on organizations’ SCA, both directly and indirectly. The indirect relationship is mediated through KM and TQM, and is serially mediated via both KM and TQM. These findings are generally consistent with the extant literature and support the notion of direct and indirect relationships between EIMC and SCA. However, the literature to date has paid little attention to these relationships. This research contributes to the knowledge concerning EIMC, TQM, and KM by providing empirical evidence of their ability to create and sustain a competitive advantage. In short, if EIMC is properly developed, it helps organizations to achieve KM, TQM and thus gain and sustain competitive advantage. Understanding the direct and indirect impacts of EIMC on SCA can positively affect organizations’ performance. Further research has been recommended to further critique an investigate the proposed model, especially in non-UAE contexts, and to extend the model by examining other mediators between EIMC and SCA

Knowledge Capturing in Design Briefing Process for Requirement Elicitation and Validation

Knowledge capturing and reusing are major processes of knowledge management that deal with the elicitation of valuable knowledge via some techniques and methods for use in actual and further studies, projects, services, or products. The construction industry, as well, adopts and uses some of these concepts to improve various construction processes and stages. From pre-design to building delivery knowledge management principles and briefing frameworks have been implemented across project stakeholders: client, design teams, construction teams, consultants, and facility management teams. At pre-design and design stages, understanding the client’s needs and users’ knowledge are crucial for identifying and articulating the expected requirements and objectives. Due to underperforming results and missed goals and objectives, many projects finish with highly dissatisfied clients and loss of contracts for some organizations. Knowledge capturing has beneficial effects via its principles and methods on requirement elicitation and validation at the briefing stage between user, client and designer. This paper presents the importance and usage of knowledge capturing and reusing in briefing process at pre-design and design stages especially the involvement of client and user, and explores the techniques and technologies that are usable in briefing process for requirement elicitation

The Information-Based View on Business Network Performance: Revealing the Performance of Interorganizational Networks

__Abstract__ In the last thirty years, global developments including advancements in ICT and process and product modularization have made the network form of organization more widespread than ever before. In many industries large vertically integrated organizations have been supplanted by flexible networks of independent organizations. In other industries and sectors, individual organizations continue to operate through the traditional organizational form of a business network. The proliferation of business networks presses the need to move theoretical development on processes and outcomes forward, beyond actor and dyadic level to the whole network level of analysis. Network performance studies however, have been scattered both across time and across management disciplines, and offer diverse concepts, measures and drivers, which slows down the theoretical build up. A related problem is that the conceptual issue of what constitutes performance on network level, has been left unaddressed. The main purpose of this dissertation is therefore to conceptualize and explain the performance of interorganizational networks. This is done by executing three studies: conceptualization research laboratory experiments and a field case study. Step by step an integrated framework is built in this dissertation that represents the information-based view on network performance and its theoretical mechanisms. This dissertation pushes the boundaries of knowledge on network performance, increases the understanding and ability of practitioners to manage their networks and sets the agenda for future network performance research

AIRM: a new AI Recruiting Model for the Saudi Arabian labour market

One of the goals of Saudi Vision 2030 is to keep the unemployment rate at the lowest level to empower the economy. Prior research has shown that an increase in unemployment has a negative effect on a country’s Gross Domestic Product. This research aims to utilise cutting-edge technology such as Data Lake (DL), Machine Learning (ML) and Artificial Intelligence (AI) to assist the Saudi labour market bymatching job seekers with vacant positions. Currently, human experts carry out this process; however, this is time consuming and labour intensive. Moreover, in the Saudi labour market, this process does not use a cohesive data centre to monitor, integrate, or analyse labour market data, resulting in inefficiencies, such as bias and latency. These inefficiencies arise from a lack of technologies and, more importantly, from having an open labour market without a national labour market data centre. This research proposes a new AI Recruiting Model (AIRM) architecture that exploits DLs, ML and AI to rapidly and efficiently match job seekers to vacant positions in the Saudi labour market. A Minimum Viable Product (MVP) is employed to test the proposed AIRM architecture using a labour market dataset simulation corpus for training purposes; the architecture is further evaluated against three research-collaborative Human Resources (HR) professionals. As this research is data-driven in nature, it requires collaboration from domain experts. The first layer of the AIRM architecture uses balanced iterative reducing and clustering using hierarchies (BIRCH) as a clustering algorithm for the initial screening layer. The mapping layer uses sentence transformers with a robustly optimised BERTt pre-training approach (RoBERTa) as the base model, and ranking is carried out using the Facebook AI Similarity Search (FAISS). Finally, the preferences layer takes the user’s preferences as a list and sorts the results using the pre-trained cross-encoders model, considering the weight of the more important words. This new AIRM has yielded favourable outcomes: This research considered accepting an AIRM selection ratified by at least one HR expert to account for the subjective character of the selection process when exclusively handled by human HR experts. The research evaluated the AIRM using two metrics: accuracy and time. The AIRM had an overall matching accuracy of 84%, with at least one expert agreeing with the system’s output. Furthermore, it completed the task in 2.4 minutes, whereas human experts took more than six days on average. Overall, the AIRM outperforms humans in task execution, making it useful in pre-selecting a group of applicants and positions. The AIRM is not limited to government services. It can also help any commercial business that uses Big Data

Knowledge and Management Models for Sustainable Growth

In the last years sustainability has become a topic of global concern and a key issue in the strategic agenda of both business organizations and public authorities and organisations. Significant changes in business landscape, the emergence of new technology, including social media, the pressure of new social concerns, have called into question established conceptualizations of competitiveness, wealth creation and growth. New and unaddressed set of issues regarding how private and public organisations manage and invest their resources to create sustainable value have brought to light. In particular the increasing focus on environmental and social themes has suggested new dimensions to be taken into account in the value creation dynamics, both at organisations and communities level. For companies the need of integrating corporate social and environmental responsibility issues into strategy and daily business operations, pose profound challenges, which, in turn, involve numerous processes and complex decisions influenced by many stakeholders. Facing these challenges calls for the creation, use and exploitation of new knowledge as well as the development of proper management models, approaches and tools aimed to contribute to the development and realization of environmentally and socially sustainable business strategies and practices