Cristina Ponsiglione

An activity-based costing approach for detecting inefficiencies of healthcare processes

Purpose – The purpose of this paper is to set out a methodological framework to investigate how the integration of an activity-based costing (ABC) logic into the pre-existent accounting system supports healthcare organizations in identifying the inefficiencies related to their diagnostic therapeutic pathways (DTP) and related reengineering interventions. Design/methodology/approach – The BPM-ABC methodological framework has been applied to the case of a specific surgery pathway, at the Orthopaedic Division of a University Hospital in Italy. Findings – The case-study described in the paper points out: first, how the Business Process Management (BPM)-ABC methodology is able to produce significant information about consumed resources and the costs of the activities, useful to highlight opportunities for DTPs improvement; second, the barriers related to a pre-existing accounting system based on cost centres that can hinder the implementation of the BPM-ABC model. Practical implications – The case study points...

An analytical framework based on AHP and activity-based costing to assess the value of competencies in production processes

In this paper we present a model based on activity based costing and analytic hierarchy process to assess the impact of individual competencies on value creation and its application to a case study of a small manufacturing firm. Namely, our model is designed to support managers to deal with the following concrete situation: suppose that a company has decided to acquire a new type of equipment/technology to improve a process and deliver a superior performance to its customers, and suppose that this change requires in turn the acquisition of one or more individual competencies. Our model will support managers to answer to these questions: what is the cost of acquiring the new competence compared with the value generated by the improved process? Is it preferable to develop the competence internally or to acquire it on the market? In general, we argue that the proposed method can support managers to lay out a systematic description of the problematic link between individual competencies, organisational capabilities and critical market performances. Through the development and application of an analytical tool, this work intends to contribute to bridge the literature on the evaluation of individual competencies with the strategic interpretation of production competencies as organisational distinctive assets for value creation and as sources of sustained competitive advantage.

Knowledge exchange processes in Industrial Districts and the emergence of networks

This paper aims at exploring conditions under which the need for knowledge exchange within a small firms’ cluster generates a structure of links between firms. We focus in particular on small firms’ clusters called Industrial Districts (IDs). Specifically, we analyze IDs with flexible specialization, in which knowledge exchange is driven by the search for complementary knowledge assets. Previous works of the authors proposed an agent-based model of IDs to explore the properties of networks emerging from the interaction of firms prompted by the search and exchange of complementary specialized knowledge. This model showed that limited relational capability, due to the small size, and an exchange mechanism solely based on the barter of complementary knowledge are structural conditions that limit individual firms’ growth in IDs with flexible specialization. This paper presents a new version of this model to analyze the role of embeddedness of relationships among IDs firms in shaping the emergent network structures. The aim of the paper is to answer to the following research questions: Can knowledge complementariness explain the emergence of a stable network of firms within a small firms’ cluster? What are the structural properties of these networks? Which role does the embeddedness of relationships among firms play in shaping the structure of emerging networks?

Learning by failure vs learning by habits: Entrepreneurial learning micro-strategies as determinants of the emergence of co-located entrepreneurial networks

Purpose The purpose of this paper is to explain the emergence of collaboration networks in entrepreneurial clusters as determined by the way entrepreneurs exchange knowledge and learn through business transactions needed to implement temporary supply chains in networks of co-located firms. Design/methodology/approach A socio-computational approach is adopted to model business transactions and supply chain formation in Marshallian industrial districts (IDs). An agent-based model is presented and used as a virtual lab to test the hypotheses between the firms’ behaviour and the emergence of structural properties at the system level. Findings The simulation findings and their validation based on the comparison with a real world cluster show that the topological properties of the emerging network are influenced by the learning strategies and decision-making criteria firms use when choosing partners. With reference to the specific case of Marshallian IDs it is shown that inertial learning based on history and past collaboration represents in the long term a major impediment for the emergence of hubs and of a network topology that is more conducive to innovation and growth. Research limitations/implications The paper offers an alternative view of entrepreneurial learning (EL) as opposed to the dominant view in which learning occurs as a result of exceptional circumstances (e.g. failure). The results presented in this work show that adaptive, situated, and day-by-day learning has a profound impact on the performance of entrepreneurial clusters. These results are encouraging to motivate additional research in areas such as in modelling learning or in the application of the proposed approach to the analysis of other types of entrepreneurial ecosystems, such as start-up networks and makers’ communities. Practical implications Agent-based model can support policymakers in identifying situated factors that can be leveraged to produce changes at the macro-level through the identification of suitable incentives and social networks re-engineering. Originality/value The paper presents a novel perspective on EL and offers evidence that micro-learning strategies adopted and developed in routine business transactions do have an impact on firms’ performances (survival and growth) as well as on systemic performances related to the creation and diffusion of innovation in firms networks.

Knowledge elicitation and mapping in the design of a decision support system for the evaluation of suppliers' competencies

Purpose – This paper aims to present a methodology for the mapping and evaluation of suppliers’ competencies and know-how. The authors operationalize the concept of organizational competence and provide companies with a customized management tool to map suppliers’ critical competencies for screening strategic from non-strategic suppliers and providing inputs for suppliers’ development. Design/methodology/approach – Competencies assessment, carried out through a fuzzy knowledge management system (VINCI), is performed through the aggregation of indicators related to the control of critical resources, the degree of implementation of critical processes, the competitive positioning and the financial situation of a supplier. Competencies description and operationalization are based on the bottom-up elicitation of the subjective knowledge managers actually use to assess suppliers’ capability. Such subjective knowledge is then validated and formalized through a top-down approach based on strategic literature. Fin...

Regional Innovation Systems: An Agent-Based Laboratory for Policy Advice

The chapter presents a computational model for the development of a self-sustaining Regional Innovation System (RIS). The computational agent-based model is the core of a virtual laboratory, called CARIS (Complex Adaptive Regional Innovation System) aiming at (1) introducing the CAS (Complex Adaptive System) approach in the analysis of RISs; (2) enabling the development of effective innovation policies able to foster the growth and innovativeness of regions. This topic is particularly relevant for the so-called lagging regions, which, despite conspicuous policy interventions, have been unable to develop a significant capability to innovate. According to the European Union, lagging regions are those regions which show a GDP per capita less than 75 % of the European average. In this chapter, the methodological approach to verify the internal coherence of the model, as well as the simulation outputs are thoroughly discussed. Results show that the code is free of evident bugs, that it works coherently with the meta-model and that the agent-based computational model is able to reproduce some stylized representations characterizing the system under investigation. Finally, the first steps of the calibration activities and some preliminary results are described. Once fully validated, the CARIS laboratory should help researchers and practitioners to better investigate what critical mass of local resources and competencies are necessary to sustain the growth of RISs and, how effective current innovation policies are and what are the most effective measures to improve the current pattern.

Mapping knowledge networks for organizational re-design in a rehabilitation clinic

The purpose of this paper is to present a social network approach for identification of micro-organizational re-design interventions to make more efficient and fluid the knowledge flow in a rehabilitation multidisciplinary team. The structural information of different kinds of knowledge networks within a team is augmented with additional analyses aimed at collecting information about the ways through which participants use knowledge, the motivation behind knowledge exchange, and the non-human knowledge sources used by subjects to perform their work. This paperwork was supported by CNCSIS – UEFISCDI, project number PNII – IDEI 810/2008.,The authors propose a definition of knowledge network including human and non-human knowledge source (documents and knowledge repositories) as it is more adequate for the analysis of knowledge flows in multidisciplary medical teams. The mapping and analysis of the network are carried out through: elicitation of knowledge flows between people within and outside the team through a structured questionnaire; mapping of the knowledge flows toward non-human knowledge sources; and identification of critical aspects and proposal of re-engineering interventions to make knowledge flow more efficient and effective.,The analysis of the critical aspects emerged in the field study identifies a number of opportunities to improve the efficiency and effectiveness of knowledge sharing through the re-design of the team network. The re-design interventions concern three main features of knowledge network: “knowledge centralization,” “Over-reliance on External experts,” “Unshared knowledge tools and sources.”,The originality of the work resides in applying social network analysis (SNA) for healthcare management settings, proving evidence and guidelines to show how healthcare organizations can benefit from the adoption of SNA-based approaches.

Configurations of factors affecting triage decision-making: A fuzzy-set qualitative comparative analysis

The purpose of this paper is to explore the configuration of factors affecting the accuracy of triage decision-making. The contribution of the work is twofold: first, it develops a protocol for applying a fuzzy-set qualitative comparative analysis (fsQCA) in the context of triage decision-making, and second, it studies, through two pilot cases, the interplay between individual and organizational factors in determining the emergence of errors in different decisional situations.,The methodology adopted in this paper is the qualitative comparative analysis (QCA). The fuzzy-set variant of QCA (fsQCA) is implemented. The data set has been collected during field research carried out in the Emergency Departments (EDs) of two Italian public hospitals.,The results of this study show that the interplay between individual and contextual/organizational factors determines the emergence of errors in triage assessment. Furthermore, there are some regularities in the patterns discovered in each of the investigated organizational contexts. These findings suggest that we should avoid isolating individual factors from the context in which nurses make their decisions.,Previous research on triage has mainly explored the impact of homogeneous groups of factors on the accuracy of the triage process, without considering the complexity of the phenomenon under investigation. This study outlines the need to consider the not-linear relationships among different factors in the study of triage’s decision-making. The definition and implementation of a protocol to apply fsQCA to the triage process in EDs further contributes to the originality of the research.

Modeling Naïve Causality In Everyday Reasonig With Fuzzy Logic

The aim of this paper is to present a new approach to the representation and elaboration of fuzzy causal reasoning. The proposed approach is based on some results obtained by several studies on causal explanation in the field of cognitive sciences. Drawing form such results, we present a fuzzy linguistic inference called generalized equivalence that permits to represent causal relationships contained in causal linguistic explanations though fuzzy relationships between antecedents and consequents. The generalized equivalence expresses the uncertainty of the causal link in an approximate way. The proposed model can be used to represent verbal explanation containing fuzzy evaluations of variables and of the relationships among them, such as in the statementusually bad weather causes a remarkable increase in car accidents, where usually, bad weather and remarkable increase are fuzzy constructs. The generalized equivalence can be applied to fuzzy causal maps to represent the intensity of causal relationships between fuzzy concepts.

The Fairness/Efficiency Issue Explored Through El Farol Bar Model

The relationship between fairness and efficiency is a central issue for policy makers. To date there is no agreement among economists whether a public policy that pursues fairness entails a loss of efficiency of an economic system, or an oriented towards efficiency policy is able to facilitate the achievement of a higher fairness. In this paper we present the fairness/efficiency issue through the analysis of four agent-based simulations that implement the El Farol Bar Model proposed by Brian Arthur in (1994). As El Farol Bar models are not interested in exploring the equity issue, we modified them by introducing a set of measures of efficiency and fairness. Particularly, we assume that fairness is a short run issue and we develop time-based measurements of fairness. The computational analysis shows that selfish agents are able to achieve an efficient use of available resources, but they are incapable of generating a fair use of them. The analysis shows that random choices of agents generate an apparent fairness, which occurs only in the long run. Thus, a suitable relationship between efficiency and fairness could be reached by a public policy which defines an appropriate pay-off matrix able to drive agents’ choices.