Reconciling internal and external satisfaction through probabilistic graphical models

2017 ◽  
Vol 9 (3/4) ◽  
pp. 347-370 ◽  
Author(s):  
Flaminia Musella ◽  
Roberta Guglielmetti Mugion ◽  
Hendry Raharjo ◽  
Laura Di Pietro
Keyword(s):  
Customer Satisfaction ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Object Oriented ◽  
Holistic Approach ◽  
Probabilistic Graphical Models ◽  
Model Parameters ◽  
Holistic View ◽  
Content Type ◽  
External Customer

Purpose This paper aims to holistically reconcile internal and external customer satisfaction using probabilistic graphical models. The models are useful not only in the identification of the most sensitive factors for the creation of both internal and external customer satisfaction but also in the generation of improvement scenarios in a probabilistic way. Design/methodology/approach Standard Bayesian networks and object-oriented Bayesian networks are used to build probabilistic graphical models for internal and external customers. For each ward, the model is used to evaluate satisfaction drivers by category, and scenarios for the improvement of overall satisfaction variables are developed. A global model that is based on an object-oriented network is modularly built to provide a holistic view of internal and external satisfaction. The linkage is created by building a global index of internal and external satisfaction based on a linear combination. The model parameters are derived from survey data from an Italian hospital. Findings The results that were achieved with the Bayesian networks are consistent with the results of previous research, and they were obtained by using a partial least squares path modelling tool. The variable ‘Experience’ is the most relevant internal factor for the improvement of overall patient satisfaction. To improve overall employee satisfaction, the variable ‘Product/service results’ is the most important. Finally, for a given target of overall internal and external satisfaction, external satisfaction is more sensitive to improvement than internal satisfaction. Originality/value The novelty of the paper lies in the efforts to link internal and external satisfaction based on a probabilistic expert system that can generate improvement scenarios. From an academic viewpoint, this study moves the service profit chain theory (Heskett et al., 1994) forward by delivering operational guidelines for jointly managing the factors that affect internal and external customer satisfaction in service organizations using a holistic approach.

The “service excellence chain”: an empirical investigation in the healthcare field

2020 ◽  
Vol 32 (6) ◽  
pp. 1623-1663
Author(s):  
Roberta Guglielmetti Mugion ◽  
Flaminia Musella ◽  
Laura Di Pietro ◽  
Martina Toni
Keyword(s):  
Customer Satisfaction ◽  
Structural Equation ◽  
Healthcare Sector ◽  
Equation Modeling ◽  
Original Research ◽  
Organizational Improvement ◽  
Content Type ◽  
Service Excellence ◽  
Synthetic Index ◽  
External Customer

PurposeThe linkage between internal and external satisfaction is an understudied topic in the service field. This study aims to address this gap by proposing an original research model, the service excellence chain (SEC), that connects the internal and external perspectives by conjoining performance-excellence models and the service-profit-chain approach. Theoretical assumptions and quantitative measures are proposed by using advanced statistical techniques.Design/methodology/approachThe SEC is investigated through an empirical study in the healthcare sector, focusing on an Italian hospital and involving two of its core units. Qualitative and quantitative approaches were used. First, internal and external customer satisfaction were separately tested through structural equation modeling. The linkage between internal and external satisfaction is then proposed by mathematically defining a synthetic index, the internal and external customer satisfaction index (IEGSI), modeled through Bayesian networks (BNs) and object-oriented BNs to provide an overall measure able to predict organizational improvement.FindingsThe distinct measured models show good internal validity and adequate fit both for patients' and employees' perspectives. The IEGSI allows rigorously connecting internal and external satisfaction by developing conjoint scenarios for organizational improvement.Originality/valueThis study proposes the SEC model as an innovative way to connect internal and external satisfaction. The findings can be useful both for private and public organizations and may provide several useful insights for healthcare managers as well as for policy-makers in relation to developing strategies for improving service quality.

Capability, environment and internationalization fit, and financial and marketing performance of MNEs’ foreign subsidiaries

2017 ◽  
Vol 24 (3) ◽  
pp. 405-435 ◽  
Author(s):  
Dessislava Dikova ◽  
Arjen van Witteloostuijn ◽  
Simon Parker
Keyword(s):  
Quantitative Research ◽  
Multinational Enterprise ◽  
Holistic Approach ◽  
Outcome Variable ◽  
Necessary Condition ◽  
Holistic View ◽  
Content Type ◽  
Marketing Performance ◽  
Mne Subsidiary ◽  
The Impact

Purpose Extant work in international business (IB) involves a partial contingency-theoretic perspective: a holistic view of the impact of bundles of contingencies on an outcome variable is missing. The purpose of this paper is to adopt a contingency approach to study multinational enterprise (MNE) subsidiary performance in the appropriate context of European transition economies at the beginning of the current millennium. Design/methodology/approach Methodologically, the authors introduce abduction as a line of inquiry into IB and management to develop new theoretical insights, and apply the novel empirical general interaction method to estimate bundle effects. In so doing, the authors contribute to the further development of a theoretical and empirical toolkit to revitalize holistic, or configurational, quantitative research in IB and management. Findings The authors find that capability fit is a necessary condition for high MNE subsidiary marketing performance, whilst environment fit is particularly critical for high MNE subsidiary financial performance. Research limitations/implications A key limitation is that this is a cross-section study. Practical implications This study offers insights as to subsidiary fit into Eastern Europe, indicating fitting entry and establishment modes. Originality/value This paper offers a novel holistic approach to IB, both in terms of theoretical and empirical methodology.

scholarly journals Indirect Causes in Dynamic Bayesian Networks Revisited

2017 ◽  
Vol 59 ◽  
pp. 1-58
Author(s):  
Alexander Motzek ◽  
Ralf Möller
Keyword(s):  
Bayesian Networks ◽  
Graphical Models ◽  
Probabilistic Graphical Models ◽  
Dynamic Bayesian Networks ◽  
Coarse Grained ◽  
Mathematical Basis ◽  
Use Of Time ◽  
Modeling Uncertainties ◽  
Spurious Results ◽  
Over Time

Modeling causal dependencies often demands cycles at a coarse-grained temporal scale. If Bayesian networks are to be used for modeling uncertainties, cycles are eliminated with dynamic Bayesian networks, spreading indirect dependencies over time and enforcing an infinitesimal resolution of time. Without a ``causal design,'' i.e., without anticipating indirect influences appropriately in time, we argue that such networks return spurious results. By identifying activator random variables, we propose activator dynamic Bayesian networks (ADBNs) which are able to rapidly adapt to contexts under a causal use of time, anticipating indirect influences on a solid mathematical basis using familiar Bayesian network semantics. ADBNs are well-defined dynamic probabilistic graphical models allowing one to model cyclic dependencies from local and causal perspectives while preserving a classical, familiar calculus and classically known algorithms, without introducing any overhead in modeling or inference.

scholarly journals Holistic View on Cell Survival and DNA Damage: How Model-Based Data Analysis Supports Exploration of Dynamics in Biological Systems

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mathias S. Weyland ◽  
Pauline Thumser-Henner ◽  
Katarzyna J. Nytko ◽  
Carla Rohrer Bley ◽  
Simone Ulzega ◽  
...  
Keyword(s):  
Dna Damage ◽  
Model Calibration ◽  
Biological Effects ◽  
Holistic Approach ◽  
Model Parameters ◽  
Calibration Model ◽  
Sources Of Information ◽  
Dna Damage And Repair ◽  
Holistic View ◽  
Successful Model

In this work, a method is established to calibrate a model that describes the basic dynamics of DNA damage and repair. The model can be used to extend planning for radiotherapy and hyperthermia in order to include the biological effects. In contrast to “syntactic” models (e.g., describing molecular kinetics), the model used here describes radiobiological semantics, resulting in a more powerful model but also in a far more challenging calibration. Model calibration is attempted from clonogenic assay data (doses of 0–6 Gy) and from time-resolved comet assay data obtained within 6 h after irradiation with 6 Gy. It is demonstrated that either of those two sources of information alone is insufficient for successful model calibration, and that both sources of information combined in a holistic approach are necessary to find viable model parameters. Approximate Bayesian computation (ABC) with simulated annealing is used for parameter search, revealing two aspects that are beneficial to resolving the calibration problem: (1) assessing posterior parameter distributions instead of point-estimates and (2) combining calibration runs from different assays by joining posterior distributions instead of running a single calibration run with a combined, computationally very expensive objective function.

scholarly journals Setting the Port Planning Parameters In Container Terminals through Bayesian Networks

2015 ◽  
Vol 27 (5) ◽  
pp. 395-403 ◽  
Author(s):  
Tomás Rodríguez García ◽  
Nicoletta González Cancelas ◽  
Francisco Soler-Flores
Keyword(s):  
Data Analysis ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Simulation Models ◽  
Probabilistic Graphical Models ◽  
Resource Planning ◽  
Container Terminals ◽  
Correct Prediction ◽  
Port Planning ◽  
Transport Logistics

The correct prediction in the transport logistics has vital importance in the adequate means and resource planning and in their optimisation. Up to this date, port planning studies were based mainly on empirical, analytical or simulation models. This paper deals with the possible use of Bayesian networks in port planning. The methodology indicates the work scenario and how the network was built. The network was afterwards used in container terminals planning, with the support provided by the tools of the Elvira code. The main variables were defined and virtual scenarios inferences were realised in order to carry out the analysis of the container terminals scenarios through probabilistic graphical models. Having performed the data analysis on the different terminals and on the considered variables (berth, area, TEU, crane number), the results show the possible relationships between them. Finally, the conclusions show the obtained values on each considered scenario.

Aligning the talent development and succession planning processes: don’t allow critical leadership talent to fall by the wayside

2015 ◽  
Vol 29 (5) ◽  
pp. 3-6 ◽  
Author(s):  
Steve Newhall
Keyword(s):  
Succession Planning ◽  
Business Strategy ◽  
Holistic Approach ◽  
Holistic View ◽  
Content Type ◽  
Potential Development ◽  
Development Plans ◽  
Survey Results ◽  
Planning Processes ◽  
Critical Leadership

Purpose – Organizations need to take a holistic view of their talent management programs, and it’s no longer sufficient to simply look at the top layers of leadership (succession planning). High potentials need to be identified early and customized plans put in place to ensure that their development is aligned to the business strategy. Design/methodology/approach – Based on a global study commissioned by Korn Ferry and conducted by Hanover research during August and September 2014. The survey covered 54 countries globally and companies ranging in size from 500 to 50,000+ employees. It generated more than 1,000 responses from business leaders at the following levels: C-suite (41 per cent), VP/SVP/EVP (42 per cent), Director (11 per cent) and Other (6 per cent). Findings – Only one third of those surveyed reported they are satisfied with the outcomes of their succession programs and the majority end up recruiting externally more often than they would like to obtain the talent they need. Analysis of current versus future skills requirements is rarely done and promotions are awarded on current performance rather than future potential. Development plans are not differentiated neither are they dynamically managed. A structured and systematic approach is needed, starting earlier in employees’ careers to ensure those who have the greatest potential are ready when they need to be. Originality/value – Organizations typically recruit externally more often than they would wish. This article, through analysis of the survey results, highlights the need for a more holistic approach with early intervention and differentiated development.

Bayesian Networks in the Health Domain

2010 ◽  
pp. 342-376 ◽  
Author(s):  
Shyamala G. Nadathur
Keyword(s):  
Machine Learning ◽  
Missing Data ◽  
Bayesian Networks ◽  
Network Model ◽  
Graphical Models ◽  
Probabilistic Graphical Models ◽  
Large Datasets ◽  
Statistical Dependence ◽  
Health Domain ◽  
New Methods

Large datasets are regularly collected in biomedicine and healthcare (here referred to as the ‘health domain’). These datasets have some unique characteristics and problems. Therefore there is a need for methods which allow modelling in spite of the uniqueness of the datasets, capable of dealing with missing data, allow integrating data from various sources, explicitly indicate statistical dependence and independence and allow modelling with uncertainties. These requirements have given rise to an influx of new methods, especially from the fields of machine learning and probabilistic graphical models. In particular, Bayesian Networks (BNs), which are a type of graphical network model with directed links that offer a general and versatile approach to capturing and reasoning with uncertainty. In this chapter some background mathematics/statistics, description and relevant aspects of building the networks are given to better understand s and appreciate BN’s potential. There are also brief discussions of their applications, the unique value and the challenges of this modelling technique for the domain. As will be seen in this chapter, with the additional advantages the BNs can offer, it is not surprising that it is becoming an increasingly popular modelling tool in the health domain.

Tourism services quality (TourServQual) in Egypt

2006 ◽  
Vol 13 (4) ◽  
pp. 469-492 ◽  
Author(s):  
Mohammed I. Eraqi
Keyword(s):  
Quality Management ◽  
Customer Satisfaction ◽  
Services Quality ◽  
Research Paper ◽  
Business Environment ◽  
Total Quality ◽  
Content Type ◽  
Internal Customer ◽  
External Customer ◽  
Tourism Services

PurposeThis research paper aims is to evaluate the customer's views related to tourism quality in Egypt. It attempts to measure the extent to which tourism business environment is creative and innovative as necessary conditions for internal customer satisfaction.Design/methodology/approachThe objectives of this research have been achieved through reviewing a number of literatures in the fields of services quality management and tourism quality measurements. The paper's outcomes have been obtained through two surveys, one to measure the satisfaction of the internal customer (employees) and the second to measure the external customer satisfaction (tourists).FindingsThe main conclusions of this research paper are: quality can be considered as a philosophy for guiding tourism organization/destination when taking decisions related to tourism services; tourism business environment in Egypt does not support the internal customer satisfaction because the absence of a suitable system for encouraging people to be creative and innovative; and in the area of the external customer satisfaction there is still a need for things to be done such as the environmental conditions improvements, internal transport quality enhancement, increasing people awareness, and improving the level of safety and security conditions.Research limitations/implicationsThere is a number of limitations which faced this paper research they are: the sample size is small, compared with the size of total population, that was reflected on the level of reliability of the research results; and the limited time allowed to the respondents was reflected on the validity of the research outcomes, because they interviewed at the last time of their journey by the time they are ready for departure.Practical implicationsA useful source of information about total quality management (TQM) and how practitioners can measure it. It provides wide guidelines for improving the quality of tourism services in total manner in Egypt.Originality/valueThis paper provides useful information that are needed for tourism services quality improvement. It offers a practical help to tourism planners and marketers in Egypt to understand the concept of TQM and how they can improve their services continually.

Introduction to Bayesian Networks and Influence Diagrams

2012 ◽  
pp. 9-32
Author(s):  
Luis Enrique Sucar
Keyword(s):  
Probability Theory ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Probabilistic Graphical Models ◽  
Dynamic Bayesian Networks ◽  
Influence Diagrams ◽  
General Description ◽  
Sequential Decision ◽  
The Core ◽  
Inference Techniques

In this chapter we will cover the fundamentals of probabilistic graphical models, in particular Bayesian networks and influence diagrams, which are the basis for some of the techniques and applications that are described in the rest of the book. First we will give a general introduction to probabilistic graphical models, including the motivation for using these models, and a brief history and general description of the main types of models. We will also include a brief review of the basis of probability theory. The core of the chapter will be the next three sections devoted to: (i) Bayesian networks, (ii) Dynamic Bayesian networks and (iii) Influence diagrams. For each we will introduce the models, their properties and give some examples. We will briefly describe the main inference techniques for the three types of models. For Bayesian and dynamic Bayesian nets we will talk about learning, including structure and parameter learning, describing the main types of approaches. At the end of the section on influence diagrams we will briefly introduce sequential decision problems as a link to the chapter on MDPs and POMDPs. We conclude the chapter with a summary and pointers for further reading for each topic.

Probabalistic Inference for Actor Centered Models

2008 ◽  
pp. 115-125
Author(s):  
Gero Schwenk
Keyword(s):  
Social Science ◽  
Bayesian Networks ◽  
Graphical Models ◽  
Empirical Data ◽  
Probabilistic Graphical Models ◽  
Probabalistic Inference ◽  
Different Levels ◽  
Area Of Application

The analysis of relations between different levels of a system is a key issue in social science simulation. Here, I discuss the contribution of different modeling methodologies to this. Special emphasis is given to the formalism of “Probabilistic Graphical Models“, resp. “Bayesian Networks“, which is both advantageous for level transitory inference and integration of empirical data. Furthermore, issues of practicability and area of application are considered. The argumentation is exemplified by demonstration of a toy-application for which explicit level-transitory statements are inferred.

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