Accepted Manuscript Title: Management accounting use and financial performance in public health-care organisations. Evidence from the Italian National Health Service Author: Manuela S. Macinati Eugenio Anessi Pessina PII: DOI: Reference:
S0168-8510(14)00084-0 http://dx.doi.org/doi:10.1016/j.healthpol.2014.03.011 HEAP 3203
To appear in:
Health Policy
Received date: Revised date: Accepted date:
28-7-2013 14-1-2014 18-3-2014
Please cite this article as: Macinati MS, Pessina EA, Management accounting use and financial performance in public health-care organisations. Evidence from the Italian National Health Service, Health Policy (2014), http://dx.doi.org/10.1016/j.healthpol.2014.03.011 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Management accounting use and financial performance in public health-care organisations. Evidence from the Italian National Health Service.
Management accounting use and financial performance
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in public health-care organisations.
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Evidence from the Italian National Health Service
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Manuela S. Macinati*
Eugenio Anessi Pessina
*Manuela S. Macinati, PhD (Corresponding author) Associate Professor
Università Cattolica del Sacro Cuore, Facoltà di Economia Largo F. Vito, 1 00168 ROMA Phone: 06.3015.5816
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Fax: 06.3015.4751 Email address: [email protected]
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Eugenio Anessi Pessina, PhD Università Cattolica del Sacro Cuore
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Facoltà di Economia
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Largo F. Vito, 1 00168 ROMA
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Phone: 06.3015.5816 Fax: 06.3015.4751
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Email address: [email protected]
Abstract: Reforms of the public health-care sector have emphasised the role of management accounting (MA). However, there is little systematic evidence on its use and benefits. To fill this gap, we proposed a contingency-based model which addresses three related issues, that is, whether: (i) MA use is influenced by contextual variables and MA design; (ii) topmanagement satisfaction with MA mediates the relationship between MA design and MA use; and (iii) financial performance is influenced by MA use. A questionnaire was mailed out to all Italian public health-care organisations. Structural Equation Modelling was performed to validate the research hypotheses. The response rate was 49%. Our findings suggest that: (i) cost-containment strategies encourage more sophisticated MA designs; (ii) MA use is directly and indirectly influenced by contingency, 2
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organisational, and behavioural variables; (iii) a weakly significant positive relationship exists between MA use and financial performance. These findings are relevant from the viewpoint of both top managers and policymakers. The former must make sure that MA is not only technically advanced, but also properly understood and along dimensions that may not fully translate into better financial results.
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Keywords: Contingency theory; MA use; MA design; performance; Italy
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appreciated by users. The latter need to be aware that MA may improve performance in ways and
1. Introduction
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Over the past decades, management accounting (MA) has increasingly gained importance within health-care organisations as a fundamental tool for the pursuit of efficiency and cost containment.
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For public health-care organisations, in particular, the adoption of MA has often been encouraged (or even required) by government policy, within the modernisation initiatives that have tried to
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reshape the public sector (New Public Management – NPM) [1,2]. Indeed, accounting innovations
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have been a fundamental component of these modernisation initiatives [2,3,4], since an association has commonly been assumed to exist between accounting information, improved
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decision-making and accountability [2] and, thereby, better organisational performance [5,6]. The NPM-inspired literature, however, has largely adopted either a normative stance – stating the recommended features and components of would-be reforms – or a descriptive one – presenting the specific features and components of actual reforms [7,8]. In this respect, MA and public health care are no exceptions. As a consequence, health-policy research has so far produced little systematic evidence on the actual use and benefits of MA in health-care organisations. Management accounting research, conversely, has produced some empirical evidence on such topics as the association between MA use and financial performance, the contextual determinants of MA use, and MA design [e.g. 9,10,11]. Most of this research has been carried out in the manufacturing context, but studies also exist that were conducted in a health-care setting [12-35]. These latter studies, in particular, do offer some meaningful contributions to both theorisation and current practice in the health-policy field. The evidence they provide, however, is still rather limited, 3
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generally circumscribed to individual variables viewed in isolation, and often inconclusive. Thus, hospital managers' use of MA has been found to contribute to financial performance [22]; MA effectiveness has been associated with contextual variables [e.g. 12-14,18,19,22,25,32]; technically refined MA systems have been found to help hospital managers cope with growing
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pressures for cost control [26,27,32]. According to other studies, conversely, MA has achieved limited success, mainly because its design failed to meet functional requirements or managerial
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needs [35]. Overall, the existing explanatory literature suggests that MA's impact on financial
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performance is affected by contextual variables (e.g. the organisation's strategic goals), MA’s own technical features (MA design), individual variables (e.g. individuals’ responses to MA practices),
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and the interactions thereof. The specific variables and relationships involved, however, have so far been insufficiently theorised and empirically investigated.
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In response to this research gap, and following Chenhall’s [36] call for more contingency-based research in service and non-profit organisations, this paper adopts a contingency approach and investigates the determinants and outcomes of MA use by public health-care managers. More
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specifically, the purpose of this paper is to propose and empirically test a comprehensive,
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contingency-based research model which addresses three related issues, that is, whether: (i) MA
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use is influenced by MA design and other contextual variables; (ii) top-management satisfaction with MA mediates the relationship between MA design and MA use; and (iii) financial performance is influenced by MA use.
Our definition of MA is drawn from the management accounting literature, where “MA refers to a collection of practices such as budgeting or product costing, while MAS [management accounting system] refers to the systematic use of MA to achieve some goal. MCS [management control system] is a broader term that encompasses MAS and also includes other controls such as personal or clan controls” [36, p. 129]. To test our model, we use data from the Italian National Health Service. The motivation for conducting this study in Italy is two-fold. On the one hand, the Italian health-care sector has undergone significant managerial reforms, although the impact of these initiatives on performance has been questioned [37,38]; within these reforms, MA has been presented as a tool that can 4
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enhance financial performance and improve efficiency. On the other hand, the strong decentralisation that has characterised the Italian National Health Service in the last two decades has produced enough variation in government policies and managerial practices to provide an excellent research setting for cross-sectional statistical analyses.
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In considering the effects of MA adoption, we focus on the financial dimension of health-care organisations' performance. In Italy and elsewhere, cost control has traditionally been a major
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health-policy goal. The current financial crisis, moreover, has further reinforced the emphasis on
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downsizing policies and austerity measures. Not surprisingly, financial results are often a key variable in evaluating top-management performance. Hence, although performance in health care
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– and particularly in publicly provided health care – obviously involves different perspectives, financial performance reflects the increasing emphasis on higher efficiency and cost containment
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and MA, with its focus on financial aspects, can potentially exert a pivotal role in reaching these objectives.
The paper’s intended contribution to the existing literature is two-fold.
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The first contribution is to health-policy research. As mentioned, the adoption of MA has often been
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encouraged by government policy, but its actual uses and benefits in health-care organisations are
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still largely unexplored. Insights into the causal paths linking context, MA, and organisational performance [39,40] would both extend existing knowledge and offer useful indications to healthcare managers and policy-makers.
The second contribution is to management-accounting research. As mentioned, management accounting research is largely focused on manufacturing. The peculiarities and complexities that characterise public health care, conversely, make it an ideal setting to study advanced topics of wider relevance for industries (namely professional services and other service industries) that are becoming increasingly important within most economies. As remarked by Abernethy and Lillis [25], moreover, health care provides a particularly suitable empirical setting in that specific structural arrangements and strategic orientations are both readily observable and recognised as having implications for other elements of control systems. In particular, the web of direct and indirect relationships linking contextual variables, MA, and financial performance, which this paper seeks to 5
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investigate, is a topic of wider relevance about which little empirical evidence has so far been collected. The paper is organised as follows. Section 2 presents a short description of the study's setting, that is, the Italian National Health Service. Section 3 provides the theoretical context for the study.
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Section 4 illustrates the research model and develops the research hypotheses. Section 5 is devoted to data and methods. Section 6 presents the empirical findings. Section 7 draws some
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conclusions. Section 8, finally, discusses the paper's research and policy implications.
2. The Italian National Health Service
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The Italian National Health Service (Servizio Sanitario Nazionale – SSN) covers the entire population, is tax-funded, and provides most care free of charge at point of service. It is a three-tier system with the Central Government at the top; 21 Regional Governments in the middle; and 265
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public health-care organisations1 at the bottom.
Since 1992, a series of reforms have been passed to introduce managerial principles and
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techniques, including a 2001 Constitutional amendment that significantly “regionalised” the SSN.
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The Regions currently define health policies; appoint public health-care organisations’ General
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Managers; provide them with goals and guidelines; fund their expenditures with regional taxes and user charges, with an equalisation fund to compensate for cross-regional differences in fiscal capacity. Individual public health-care organisations, in turn, have also gained greater autonomy, although with large cross-regional differences and a more recent, generalised tendency towards recentralisation at the regional level.
From an accounting perspective, public health-care organisations have traditionally relied on cashand commitment-based budgeting and reporting. Between 1992 and 2002, however, they gradually abandoned such bases to introduce accrual-based financial and management accounting. 1
Public health-care organisations, in turn, come in four types: (i) Local Health Authorities (Aziende Sanitarie Locali – Asl), each responsible for the health of the whole population in a given area and consequently acting partly as providers – through their own personnel, hospitals, and other facilities – and partly as commissioners; (ii) Hospital Trusts (Aziende Ospedaliere – AO), providing inpatient care and hospital-based outpatient care; (iii) Public Teaching Hospitals (Aziende Ospedaliero Universitarie – AOU), combining the services of a hospital with the education of medical students and consequently owned by or affiliated with a medical school; and (iv) Public Research Hospitals (Istituti di ricovero e cura a carattere scientifico - Irccs and Centri di ricerca), combining the services of a hospital with advanced medical research.
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Italian public health-care spending has traditionally been fairly low and still is (2,400 US$ PPP and 7.2% of GDP in 2012: OECD Health Data 2013). The deteriorating conditions of public finances, however, have emphasised the need for further cost containment policies. Following the 2001 Constitutional amendment, in particular, Regional Governments have been required to break even
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and have been subjected to constraints and sanctions if they fail to do so (e.g. an automatic increase in their own tax rates or a more general loss of autonomy, under a “financial recovery
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plan” supervised by the Central Government, in exchange for a partial bail-out). These constraints
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and sanctions, moreover, have become stronger and stronger over time. Individual public healthcare organisations, in turn, have similarly been expected to break even. The Regions in better
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financial conditions, conversely, have been able to claim further degrees of freedom from Central Government oversight. Financial results have thus been increasingly viewed as a key component
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of performance. MA use, in turn, has been increasingly perceived as pivotal in reaching these
3. Theoretical framework
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results.
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To explain the potential determinants of MA use in public health care and its outcomes, we rely on
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the contingency approach. The contingency approach is not a theory per se, but rather a general idea, “a framework for investigating identified factors for which we have a priori intuition based on other organizational, economic and sociological theories” [41, p.42; see 36 for a critical review]. Contingency-based research contends that an organisation’s structure is contingent upon contextual variables and that the different components of an organisation must “fit” with each other for the organisation to perform adequately [42]. The idea that performance depends on the fit between organisational context and structure is central to the contingency view. With specific respect to MA, the identification of the key contextual variables can be traced to the works of various organisational design researchers [43-46], which have subsequently found their way into the management control literature. Based on the premise of non-universality of management control systems, researchers have set out to investigate how different variables, such as the nature of the external environment as well as the organisation's 7
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structure, size, technology, and strategy, affect MA design [e.g. 11, 47-58]. The findings of these studies have been varied, but they generally support the existence of relationships between contextual variables and MA [see 36 for a review], although some of these relationships may be weak [59]. Accordingly, the basic premise of the contingency approach to MA is that MA (or, more
by the relevant organisation and this, in turn, affects performance [60].
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generally, any management control system) is affected by the particular set of circumstances faced
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Contingency-based accounting studies have generally assumed that “fit is the result of a natural
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selection process that ensures that only the best-performing organisations survive to be observed at any point of time” [61, p. 307]. In other words, when appraising fit, these studies do not examine
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whether the context-structure relationship affects performance, because the impact of fit (between management control systems and contingency factors) on effectiveness is assumed as intrinsic
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and only the best-performing organisations can survive. These studies, in other words, adopt a “congruency” theory application in that a simple unconditional association is predicted among variables [62,63].
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This congruency theory application, however, has been criticised because "signalling survival of
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the fittest is too crude a proxy for performance" [64]. It has consequently been suggested that
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contingency-based accounting research should employ organisational performance or other measures of effectiveness as the dependent variable [36]. Correspondingly, accounting researchers should analyse the "conditional association of two or more independent variables with a dependent outcome" [62, p. 514] and contingency models should be developed in order to ascertain the impact of the fit between context and structure on performance. The concept of outcome, in turn, is itself problematic. Although the outcome of MA has often been interpreted as organisational performance, contingency-based studies need to consider that the effects of MA on performance are “indirect and [are] conveyed to outcome criteria via some intervening constructs which links the variables” (65, p. 225-226). In particular, according to Chenhall [36, p. 135], contingency-based accounting studies should “first establish adoption and use of MCS, then [...] examine how they are used to enhance decision quality and finally
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investigate links with organisational performance”. This is the starting point for our model, which is presented in the next Section.
4. Model development and research hypotheses
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4.1 The model
The contingency-based model for our research is presented in Figure 1. It is a comprehensive
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model which includes: (i) multiple contingent variables; (ii) different aspects of MA that should be
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analysed following Chenhall [36]; and (iii) organisational performance as the dependent variable. In operationalising the variables, we adopted an intervening approach [36,62]. Specifically, we
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analysed the causal paths linking context, structure, and performance in order to identify the determinants of MA design and use and to explain the relationship between MA and performance
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through the direct and indirect effects of the intervening variables. Insert Figure 1 here
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The model involves three contingency variables (exogenous constructs). The variable “strategy”
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stems from conventional theories of organisational structure, referred to as the strategy-structure-
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performance paradigm. The variable “region” reflects the influence that Regional Governments exert on the adoption, design, and use of MA by individual health-care organisations, both indirectly (e.g. through the importance assigned to financial performance within regional policies) and directly (e.g. through guidelines on MA design and incentives for MA adoption). The variable "organisational size”, finally, was included for its reported contingent significance in several prior accounting studies [35,49,66].
The "heart" of the model includes several variables related to MA characteristics, mental models, and behaviours associated with MA, respectively labelled as "MA design", "satisfaction with MA", and "MA use", and modelled as endogenous constructs. The model assumes a relationship between MA and performance. The difficulties associated with measuring the influence of MA on performance, however, suggested employing a mediating variable, namely MA use, the omission of which would have “constitute(d) a blind spot in the 9
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framework” [67, p. 265]. The underpinning assumptions are that (i) MA cannot contribute to performance if it is not used and that (ii) its use, in turn, is influenced by individual satisfaction with the accounting system.
as previously discussed and consistent with [60, 68].
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The remainder of this Section presents the research hypotheses.
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The last element of the model is financial performance, which is viewed as the outcome variable,
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4.2. Contextual variables and MA design
Contingency-based accounting studies generally support the existence of a relationship between
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contextual variables and MA design, despite some weaknesses and fragmentary conclusions [59]. More specifically, the external environment in which organisations operate has been argued to
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affect MA design in terms of certain information characteristics [51,69-71]. This is because MA is intended to address decision-makers’ information needs, which are supposed to be influenced by the external environment. The literature (in general, but also with specific respect to health care
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[32]) highlights four critical intrinsic characteristics (or attributes, or scope) of accounting systems
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that are significant in assisting managerial decision-making and can consequently be used to
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describe MA design: (i) the level of detail provided; (ii) the ability to disaggregate costs according to behaviour; (iii) the frequency of information reporting; and (iv) the extent to which variances are calculated. In particular, we consider the following three links between the external environment (contingency variables) and MA design: (i) the link between strategy and MA design; (ii) the link between organisational size and MA design; (iii) the link between Regional policies and MA design.
- The link between strategy and MA design Contingency-based research contends that strategy influences MA design [e.g. 72,73]. In analysing the relationship between strategy and MA design, contingency-based accounting research highlights that certain designs are more consistent with certain strategies, since different strategies require different internal structures and processes, including appropriate MA information [e.g. 11,35,53,74-77]. In particular, organisations that emphasize cost strategies are supposed to 10
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require MA information that focuses on enhancing operating efficiencies and cost minimization (narrow scope of MA, [11]). Organisations that pursue differentiation strategies, on the contrary, mostly rely on external, future-oriented accounting information (broad scope of MA, [11]). With specific reference to health care, Pizzini [32] found that hospitals following a low-cost strategy need
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a more functional and sophisticated MA design because managers will require more articulated cost-oriented information to control costs [32,78]. On the other hand, hospitals following a
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differentiation strategy can be expected to focus their resources on clinical care to the detriment of
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MA sophistication. Similar results have been reported by Abernethy and Brownell [22] and by Boulianne [33].
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On the basis of the above discussion, we put forward the following hypothesis: H1: Strategy has a direct effect on the technical features of MA design (path 1-4), with cost-
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containment strategies encouraging MA sophistication.
- The link between organisational size and MA design
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Contingency-based accounting research has examined the role of organisational size in MA design
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[e.g. 47,49,79], finding that size generally encourages MA sophistication, specialization, and use,
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for reasons of both motive and opportunity. In terms of motive, larger organisations are more complex and must cope with greater control issues. In terms of opportunity, they have access to greater resources and can benefit from economies of scale resulting from more functional and sophisticated MA designs. To some extent, these arguments have also been confirmed with specific reference to health-care organisations. Hill [24], for instance, claimed that larger hospitals will draw greater benefits from functional cost systems because they can spread the fixed costs of system development over more beds. Accordingly, the following hypothesis is proposed: H2: Organisational size has a direct effect on the technical features of MA design (path 2-4), with greater organizational size encouraging MA sophistication
- The link between Regional policies and MA design 11
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The institutional environment, which is characterized by the elaboration of rules, practices, symbols, beliefs, and normative requirements to which individual organisations must conform in order to receive support and legitimacy, can be expected to affect public hospitals' management control systems. Building on this theoretical premise, Abernethy and Chua [20] adopted a
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contingency-based approach to analyse whether MA design in public health-care organisations is shaped by politics and stakeholder power. Their results demonstrate that the accounting control
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system is a function of the institutional environment’s pressures and that these pressures were
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exerted primarily through state funding agencies. Thus, there are theoretical and empirical reasons to believe that MA design in public health care can be contingent on the institutional environment
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[see for example 20,23,29,36].
In Italy, as described in Section 2, jurisdiction over health care has been largely devolved to the 21
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Regions. As a consequence, the performance objectives and management practices of individual health-care organisations will be strongly affected by Regional policies and guidelines. The Regional environment thus becomes an important context element for MA design. Particularly
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relevant is the presence of Regions which, due to their critical financial performance, have been
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partially stripped of their autonomy and subjected to "financial recovery plans" under strict Central
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Government oversight. In these Regions, public health-care organisations have been pressured to invest in sophisticated MA designs in order to provide more detailed cost information to the Central and Regional governments and to satisfy stakeholder demands for efficiency. Accordingly, we posit that:
H3: Regional policies have a direct effect on the technical features of MA design (path 3-4), with financial recovery plans encouraging MA sophistication
4.3. MA use and its determinants According to Otley [80, p.122], the effectiveness of an organisation's MA system depends on “the appropriateness of its technical characteristics to the particular organisational and environmental circumstances”, but also on “the way in which organisational participants make use of the information that it provides”. 12
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Despite recognizing the importance of accounting and control systems use [61,80,81], the empirical literature has devoted little attention to its determinants [74]. We posit that the use of MA for decision-making depends directly or indirectly on a number of variables including contextual,
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technical, and individual-level variables.
- The links between contextual variables and MA use
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Contextual variables can exert a direct influence on the use of MA information. The management
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accounting literature, in particular, suggests the presence of a direct link between strategy and MA use. For example, Chenhall and Langfield-Smith [72] found that the use of management
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accounting systems varies according to the strategy pursued. Health-care organisations pursuing cost-based strategies can consequently be expected to make a more intensive use of MA
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information in order to monitor and contain costs.
In addition to the direct effect of strategy on MA use, we expect that MA design intervenes in the relationship between strategy and MA use. As already stated, different strategies can be expected
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to affect the configuration of MA and of the wider management control system, in order to provide
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decision-makers with the information they need. With specific respect to health care, for instance,
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Kettelhut [82] and Hill [24] found that hospitals operating in markets with strong competition and/or significant penetration from managed-care organisations produced more extensive and detailed cost information and used these information in response to greater external pressures to control costs. Therefore, in addition to the direct effect of strategy on MA use, we posit that strategy affects MA design and this, in turn, affect the use of MA . Hence, the following research hypotheses are suggested: H4: Strategy has a direct effect on MA use (path 1-6), with cost-containment strategies encouraging MA use H5: MA design mediates the relationship between strategy and MA use (path 1-4-6)
In addition, as organisations become larger, the need for managers to handle great quantities of information increases to a point where they have to institute rules and other controls [79], not least 13
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because size generally implies complexity. The larger the organisation, therefore, the greater the reliance on formal controls, including an emphasis on MA information to assist in making and implementing decisions. Thus, we can expect a positive relationship between organisational size and the extent of MA use. Hence, we posit that:
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H6: Organizational size has a direct and positive effect on MA use (path 2-6)
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- The links between MA design, top-management satisfaction with MA, and MA use
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Both MA design and management satisfaction with the information that MA provides can influence MA use.
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On the one hand, the technical features of MA design will affect its ability to provide decisionmakers with the information they need and, thus, MA use. To put it differently, if MA design is
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technically inadequate, the information that MA provides will not be used, because it will be perceived as unable to support managerial decision-making. With respect to health care, in particular, the literature has strongly suggested the use of highly refined cost systems to help
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hospital managers respond to growing pressures for cost control [19,32].
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Thus, the following hypothesis is developed:
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H7: MA design has a direct and positive effect on MA use (path 4-6)
At the same time, MA effectiveness in supporting decision-making has been shown to depend not only on the technical features of MA design, but also on MA's coherence with managers’ mental models [83]. Management satisfaction with MA must consequently be viewed as an another important determinant of MA use. User satisfaction is the “extent to which users believe that the information system available to them meets their information requirements” [84]. User satisfaction includes an affective response towards the delivery of information [84,85] in that it reflects the user’s feelings about the information system’s usefulness [86]. Based on these premises, we expect user satisfaction to be influenced by the technical features of MA design and, in turn, to influence MA use. In addition, we posit that user satisfaction mediates the relationship between MA design and MA use. More specifically, if managers perceive that the information provided by their 14
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MA system meets their information requirements, they will be satisfied with it, and will consequently be more likely to use it for decision-making and control purposes [86,87,88]. Accordingly, we posit the following hypotheses: H8: MA design has a direct and positive effect on satisfaction with MA (path 4-5)
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H9: Satisfaction with MA mediates the relationship between MA design and MA use (path 4-5-6)
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H10: Satisfaction with MA has a direct and positive effect on MA use (path 5-6)
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4.4 MA use and performance
The ultimate purpose of MA implementation is to improve organisational performance, including
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financial performance. However, there is little empirical evidence on the positive relationship between MA characteristics and financial performance, also because a large portion of MA benefits
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is generally qualitative and intangible [89].
To a large extent, the impact of MA on performance will depend on the way in which organisational participants make use of the information they receive [90-93], so much so that “the use of control
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information can be more significant than the formal design of the control system” [67, p.274]. In
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performance.
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addition, MA use can also be expected to act as a mediating variable linking MA design to
Following our choice to focus on financial performance, the following hypotheses are consequently suggested:
H11: MA use has a direct positive effect on financial performance (path 6-7)
H12: MA use mediates the relationship between MA design and financial performance (path 4-6-7)
5. Methods 5.1 Data
To test the hypotheses, questionnaires were sent personally to the General Managers of all Italian public health-care organisations (n=265). Personalizing the survey was intended to increase the response rate [94,95].
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Consistent with the research framework, the questionnaire (see Appendix 1) was made up of four Sections addressing: (i) strategy, (ii) MA design, (iii) top-management satisfaction with MA, and (iv) MA use for decision-making. The questionnaire also included a cover letter explaining the purpose of the study and a preliminary Section intended to collect data on the respondents and their
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organisations. Geographic location (Region), size, and financial performance were not addressed in the questionnaire as they could be gathered from official sources. A recall to the General
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Managers who had not answered within three weeks was then conducted using a combination of
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mail, email, and telephone [73].
A total of 131 questionnaires were returned, with a response rate of 49%. This response rate is
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similar to those reported in other management accounting surveys [e.g. 90,96]. In addition, it complies with Baruch's [97] recommendations in that Baruch reported an average (standard
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deviation) response rate for surveys of top managers of 35.5% (13.3%). Nevertheless, two sets of tests were conducted to rule out the presence of non-response bias. First, following Oppenheim [98, p.34], a comparison was performed between the mean scores of
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early and late responses. To this end, respondents were divided in two halves based on the date of
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receipt of the completed questionnaire; t-tests were then performed on the continuous variables
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included in the questionnaire (strategy, MA design, top-management satisfaction with MA, and MA use for decision-making). No statistically significant differences were found between the mean scores of the two halves.
Second, the sample was analysed with reference to the main stratum variables: geographic location (North, Centre, South), organisational type (see footnote 1), hospital size (total operating revenues, see par. 5.2), and financial performance (operating expenses, see par. 5.2). Chi-square tests did not find any statistically significant differences between the respondents and the entire population in terms of either geographic location (! 2= 4.5, p = .13) or organisational type (! 2= 1.28, p = .52 ). Similarly, t-tests did not find any statistically significant differences between the respondents and the entire population in terms of hospital size (t = -.009; p = .99), and financial performance (t = .83; p = .41).
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Among responding organisations, operating revenues averaged m€ 388.55 (SD: 294.16). 41.4% were located in a Region under a financial recovery plan. The mean age of respondents was 53 years. The respondents had held their current positions for an average of 3.4 years. Roughly 40%
5.2 Measures
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The measures employed in the empirical analysis are described below.
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of the respondents had a background in medicine; 10% were female2.
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Strategy. Following previous approaches to strategy measurement in health care [e.g. 25, 99,100], we employed the measure developed by Miles and Snow [77]. Miles and Snow developed this
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instrument to assess an organisation’s overall strategic orientation. To this end, respondents were asked to indicate the degree of emphasis that their firms had given to prospector-type and
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defender-type strategic priorities. Consistent with Abernethy and Lillis [25], we used Miles and Snow's measure not to ascertain whether a health-care organisation fits into the “prospector” or “defender” classification, but rather to assess the degree to which it is committed to quality service
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or efficiency/cost containment strategies. Thus, our questionnaire presented health-care managers
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with a brief profile of each strategy and asked them to rate, on a seven-point Likert scale, how well
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each profile described their organisations.
Organisational size. In health care, size is often proxied by the number of hospital beds or admissions. Italian public health-care organisations (especially ASLs, see footnote 1), however, also perform significant public-health and outpatient activities. Size was thus measured by the total annual operating revenues of each health-care organisation. Region. Regional features and policies were summarized by a dummy variable for whether the Region was subject to a financial recovery plan. MA design. MA design was measured according to the four "attributes" identified in Section 4: (i) level of detail provided; (ii) ability to disaggregate costs according to behaviour; (iii) frequency of
2
A correlation analysis of the respondents’ demographic variables with the variables employed in the questionnaire was performed with the aim to detect potential spurious effects. No significant associations were observed. In performing the correlation analysis we considered the type of the variables used (if they were continuous or discrete).
17
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information reporting; and (iv) extent to which variances are calculated [see 32]. For each attribute, respondents were asked to assess their MA systems over a seven-point Likert scale. Top management satisfaction with MA. Doll and Torkzadeh [87] identified five components of user satisfaction with information systems: content, accuracy, format, ease of use, and timeliness.
ip t
For each component, they also identified a number of specific items. These items were slightly adapted to better fit the purpose and context of our study3. For each item, respondents were asked
cr
to express their satisfaction using a seven-point Likert scale.
us
Use of MA. Despite its importance, the concept of “MA use” has not been well developed in the management accounting literature. In order to investigate the extent to which General Managers
an
use MA information for specific decision-making and control purposes, four questions were constructed. For each question, respondents were asked to rate their use of MA over a seven-point
M
Likert scale.
Performance. Performance is a multi-dimensional concept, whose attributes change over time as well as across stakeholders and organisations. In public organisations, defining and measuring
d
performance is even more complex, because stakeholder expectations are heterogeneous, cover
te
multiple issues, often produce a wide range of positions on each issue, shift rapidly over time, and
Ac ce p
are difficult to specify and prioritise. The introduction of MA, however, has generally been expected to improve the financial conditions of public health-care organisations, not because public hospitals should pursue profit as their ultimate goal, but rather because financial viability is a prerequisite for the provision of adequate patient care. Improved financial performance can thus be viewed as a key outcome of MA adoption by public health-care organisations. In this study, financial performance was expressed in terms of operating expenses scaled by total operating revenues.
5.3 Statistical analysis The data were investigated by means of confirmatory factor analysis (CFA) and structural equation modelling (SEM). According to the two-step approach recommended by Anderson and Gerbing [101], in particular, CFA was employed to assess the adequacy of the measurement model, while 3
In particular, the questions “Is the system user friendly?” and “Is the system easy to use?” were omitted, as they did not appear to be particularly useful in assessing General Managers’ satisfaction with MA.
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SEM was subsequently used to test the research hypotheses by aggregating the items reflecting a common construct (mean values of the variables). Before performing CFA and SEM, the data set was verified for compliance with the main assumptions underlying these techniques [102]. Since the data were found to moderately deviate
ip t
from a normal distribution, in particular, robust maximum likelihood estimation was used in both CFA and SEM [103]. A similar approach was used by Castañeda et al [104] and is recommended
us
cr
by Curran et al. [105].
6. Results
an
6.1. Confirmatory factor analysis
Initially, a CFA model was evaluated using all the items in the questionnaire. However, the CFA
M
model fit indices did not fully meet the cut-off values recommended by the most recent literature. Presumably, this was because a model composed of many parameters will often show computational problems, poorer fit, and increased measurement errors, especially when the
d
sample size is small or moderate [106]. These issues can be tackled using partial disaggregation
te
models [107]. The aim of partial disaggregation procedures4 is to reduce the number of observed
Ac ce p
variables and parameters included in CFA models [for a complete discussion see, for example, 108,109].
Using partial disaggregation5, CFA results showed a Satorra-Bentler chi-square statistic of 50, returning a significant p-value. Bagozzi and Yi [110], however, noted that chi-square is very sensitive to sample size. Marsh et al. [111], moreover, criticised the relevance of chi-square statistics for model evaluation and suggested the use of other goodness-of-fit measures. Among these, the chi-square to degrees of freedom ratio was 1.3 (df: 38). CFA fit indices were greater than the recommended value of 0.95 (NNFI=0.97; CFI=0.98; IFI=0.98; GFI=0.96). RMSEA and SRMR were both 0.05, showing an adequate model fit [83,84,85].
Partial disaggregation procedures use items aggregated randomly to form three indicators per construct. Some of the variables considered in the model were defined using only one item. These were excluded from CFA.
4 5
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Table 1 presents the robust maximum likelihood standardized loadings, the item reliabilities, the derivative statistics of composite reliability, and the average variance extracted (AVE), as well as the correlations among the CFA factors and Cronbach's alpha coefficients. Table 1 also reports the correlations between the other variables included in the model.
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Insert Table 1 here
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The results summarised in Table 1 were used to confirm the measurement model's reliability,
us
convergent validity, and discriminant validity.
Reliability was assessed at two levels: item reliability and construct reliability. Single-item reliability,
an
which refers to the amount of variance in an item due to underlying construct rather than to error, was always greater than 0.50, thus supporting item reliability. Construct reliability, which refers to
M
the degree to which an instrument reflects an underlying factor, was assessed by composite reliability. Composite reliability was greater than the recommended value of 0.70 for each and so was Cronbach's alpha, thus supporting construct reliability. Having ensured that the scales meet
d
the necessary levels of reliability, scale validity was assessed. To this end, convergent and
te
discriminant validity were tested. Convergent validity, which assesses the degree to which
Ac ce p
dimensional measures of the same concept are correlated, was measured by the Average Variance Extracted (AVE). AVE values were greater than 0.5 thus demonstrating that convergent validity was not an issue. Discriminant validity, which is the degree to which conceptually similar concepts are distinct, was assessed by comparing the AVE with the maximal squared correlation of CFA factors (Table 1, correlations 1-4) [112]. In particular, the maximal squared correlation of CFA factors (0.64) was below the minimal AVE (0.66), thus satisfying the discriminant validity criterion of Fornell and Larker [113].
Finally, procedural and statistical arrangements were employed to minimize the occurrence of common method bias (CMB) [114]. The procedural arrangements were related to the design of the questionnaire, while the statistical arrangements included Harman’s single-factor test, which was conducted by performing exploratory factor analysis (EFA) on all the items of the study. The examination of the unrotated factor structure revealed four factors with eigenvalues above one, 20
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with no single dominant factor explaining a majority of the variance [114]. Therefore, CMB did not appear to be a problem for this study.
6.2. Structural equation model
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SEM analysis was carried out in three main steps.
In the first step, the full theoretical model shown in Figure 1 was tested, imposing the causal
cr
structure of the hypothesised model on the set of observed data. The Satorra-Bentler chi-square
us
statistic was insignificant (9.7, p=0.20), the chi-square to degrees of freedom ratio was 1.38 (df: 7), and the fit indices (NNFI=0.96; CFI=0.98; IFI=0.99; GFI=0.98; RMSEA=0.05; SRMR=0.04) showed
an
that the structural model fitted the data. Table 2 presents the standardized path coefficients and their statistical significance levels for the full causal model6. Six of the ten causal paths specified in
M
the full model were found to be statistically significant, although to different extents, with positive path coefficients: (i) strategy and MA design; (ii) strategy and MA use; (iii) MA design and MA use;
performance.
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(iv) MA design and satisfaction with MA; (v) satisfaction with MA and MA use; and (vi) MA use and
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Insert Table 2 here
Ac ce p
In the second step, an additional confirmatory post ad hoc analysis was performed using nested models in order to identify the most parsimonious model [101]. The final structural model shown in Fig. 2 is the most parsimonious and excludes the non-significant structural paths from the initial full causal model. In the final model, the Satorra-Bentler chi-square statistic remained insignificant (15.26, p=0.10), the chi-square to degrees of freedom ratio was 1.76 (df: 13), and the values of the fit indices (NNFI=0.97; CFI=0.99; IFI=0,99; GFI=0.98; RMSEA=0.03; SRMR= 0.04) showed a good fit to the data. The chi-square difference between the two models was not significant (Δχ2(4) =5.56); the AIC (Akaike Information Criterion) value in the final model was 51, compared to 53 in the full causal model; the final model thus represents the best fit to the data overall. Under the final model, the list of statistically significant paths did not change from the full initial model, nor changed the
6
Although no hypothesis was developed about the relationship between MA design and performance, the related path was added to test the MA design-performance link via the indirect effect of MA use.
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signs of their standardized coefficients (Table 3). Hence, hypotheses H1, H4, H7, H8, H10 and H11 were supported. Insert Figure 2 here Insert Table 3 here
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In the third and final step, an analysis was conducted on standardized direct, indirect, and total effects in order to test hypotheses H5, H9, H12. The indirect effects were obtained via Lisrel output
cr
using the product of coefficients method. The significance of indirect effects was determined with
us
PRODCLIN software using the M-test for asymmetric confidence intervals [115]. Results showed that the path between MA design and MA use via the indirect effect of Satisfaction with MA was
an
significant (indirect effect = 0.27). Similarly, results showed the significance of the indirect effect of MA design in the relationship between Strategy and MA use (indirect effect = 0.26). Both
M
hypotheses H5 and H9 were thus supported. In contrast, H12 was not supported since the indirect effect of MA use in the relationship between MA design and Performance was not significant (indirect effect = 0.11).
te
d
Insert Table 4 here
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7. Discussion and conclusions
Research on MA in the public health-care sector has often taken a normative or a descriptive stance, without a strong and clear reference to theory. The existing empirical evidence on the use and benefits of MA, therefore, is still rather limited, generally circumscribed to individual variables viewed in isolation, and often inconclusive. Consistent with Chenhall’s [36] call for more contingency-based research in service and nonprofit organisations, the purpose of this paper was to partially fill this gap by investigating the complex web of relationships that link contextual variables, MA’s technical features, MA use, individual-level variables, and organisational performance, so as to identify both the determinants of MA use and its effects on performance. To this end, we developed a contingency-based theoretical model and tested it using data on MA practices in Italian public health-care organisations.
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More specifically, our model was intended to test three sets of relationships: (i) the impact of three contingent variables (strategy, size, and Regional context) on MA design; (ii) the impact of MA design on MA use by health-care managers, be this impact direct or mediated by manager satisfaction with their organisation's MA, as well as the relationship between strategy and MA use
ip t
via MA design; and (iii) the direct relationship between MA use and financial performance, as well as the relationship between MA design and financial performance as mediated by MA use.
cr
With respect to the first issue (impact of strategy, size, and Regional context on MA design), only
us
strategy was found to matter. Consistent with research carried out in the private sector and with the results obtained by Pizzini [32] for US hospitals, cost-containment strategies were found to
an
encourage more sophisticated MA designs, probably because public health-care managers require more information for cost control purposes. This finding suggests that MA adoption by hospitals
M
cannot be viewed as a merely ceremonial process [17]. On the contrary, hospitals seem to accept that MA can support the pursuit of strategies and to consciously invest on MA design when cost containment becomes their priority. Interestingly, no association was found between organisational
d
size and MA design, possibly because Italian public health-care organisations are all fairly large
te
and must consequently cope with comparable decision-making and control issues. Similarly, no
Ac ce p
association was found between the relevant Region being subject to financial recovery plans and MA design, hopefully because financial recovery plans have forced the "weakest" Regions to invest in management tools and to partially catch up with the "best performers", at least in this regard.
With respect to the second issue (the relationship between MA design and MA use, be it direct or mediated by managers' satisfaction with MA), both direct and indirect impacts were found to be positive and statistically significant. In addition, MA use was also found to be encouraged by the pursuit of cost-containment strategies both directly or indirectly via the mediating role of MA design. Thus, contingency, organisational, and behavioural variables all seemingly come into play and complement one another to influence MA use. Interestingly, satisfaction with MA is strongly and directly influenced by MA design. Since satisfaction with MA can be considered a subjective measure of information system success in organisations [86], this result suggests that higher MA 23
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sophistication can influence the perceived effectiveness of MA, although MA use will also depend upon the extent to which the health-care organisation focuses on cost-containment strategies. Finally, with respect to the third issue (the impact of MA design and use on financial performance), no statistical significance was found for the direct and indirect relationships between MA design
ip t
and financial performance. Conversely, a positive relationship was found between MA use and
us
not MA design per se that influences performance, but its use.
cr
financial performance, although with weak statistical significance. These results confirm that it is
8. Implications
an
The idea that the adoption of private-sector practices and techniques by public-sector organisations, per se, cannot be expected to improve performance, is not entirely new. In the
M
existing literature, however, this result has often been attributed to a merely ceremonial introduction of management techniques [19]. We add to this literature and to management accounting research by: (i) suggesting the existence of a joint effect of contingency, organisational,
d
and behavioural variables on MA use, and (ii) providing modest evidence of a positive relationship
te
between MA use and financial performance.
Ac ce p
These results are relevant from the viewpoint of both managers and policymakers. From a managerial perspective, these results suggest that, to avoid a merely ceremonial introduction of MA, MA use should be encouraged through a two-pronged approach: (i) develop a technically sound MA system, but also (ii) make sure that managers appreciate its qualities and learn to fully exploit its potential.
From a policy viewpoint, this study provides policymakers with two meaningful indications. First, preventing a merely ceremonial adoption of MA is also a matter of policy. According to our findings, when efficiency and cost containment become a real priority, as opposed to being a purely rhetorical goal, MA design and use are both significantly and positively affected. For efficiency and cost containment to be a real priority, however, policymakers need to design appropriate incentives in terms, for instance, of funding criteria for individual public health-care organisations and reward systems for their General Managers. Given the importance of effectiveness and equity in publicly 24
Page 24 of 39
funded health care, however, this is a rather complex task, the obvious risks being to excessively encourage cost containment at the expense of service quality [31] and to further widen the gap between the best and the worst performing organisations by systematically rewarding the former and penalising the latter. Second, to the extent that efficiency and cost containment are indeed a
ip t
priority, national and regional policies that encourage MA adoption find at least some support in our findings in that MA use has been shown to positively affect financial performance. Admittedly, the
cr
statistical significance of the relationship between MA use and financial performance is weak, but
us
this is not particularly surprising. In general, as mentioned in Section 4, there is little empirical evidence of the positive relationship between MA characteristics and financial performance,
an
because a large portion of MA benefits is qualitative and intangible. With specific respect to public and non-profit organisations, moreover, efficiency gains will generally be used not to increase net
M
income, but rather to improve service quantity and quality, unless (as is the case for many Italian health-care organisations) financial conditions become so critical that improving net income (i.e., reducing deficits) is indeed a key priority. In other words, MA use may reasonably be expected to
te
translate into better financial results.
d
improve organisational performance in ways and along dimensions that do not meaningfully
Ac ce p
Our focus on financial performance - and the resulting exclusion from the model of variables that capture effectiveness-oriented initiatives - indeed represents the main limitation of this study. Future research could include these variables and focus on longitudinal studies in order to observe causal linkages between variables over longer periods of time. Despite these limitations, this study has improved our understanding of MA use, its determinants and its effects; it has also shed some light on the impact of reforms and policies currently under implementation in health care.
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[90] Baines A., Langfield-Smith K. Antecedents to management accounting change: A structural equation approach. Accounting, Organizations & Society 2003;28:675-698. [91] Christensen J., Demski J. Accounting theory: An information content perspective. McGrawHillIrwin, 2002. [92] Christensen P., Feltham G. Economics of Accounting. Kluwer, 2003. 32
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Appendix Research areas
Variables
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Please, place healthcare organization along a seven-point scale 1 = not at all, 7 = completely “Hospital A believes that doing the best job possible in its existing range of services. Its objectives are achieving lower costs, achieving lower costs for specific inputs (personnel, pharmaceuticals …) and achieving higher efficiency”
To what extent does the cost accounting system provide data that allow you to analyze costs 1 = not at all, 7 = completely The cost accounting function can easily customize reports to the specification of users? 1 = strongly agree, 7 = strongly disagree Does your cost system have a formalized method of distinguishing costs according to their behaviour? 1 = not at all, 7 = completely How often does the cost accounting system report information? 1=rarely, 7=frequently To what extent does your cost system provide data that allow you to analyse variances? 1 = not at all, 7 = completely Does the MAS provide the precise information you need? (1 = not at all, 7 = completely) Does the information content meet your needs? (1 = not at all, 7 = completely) Does the MAS provide reports that seem to be just about exactly what you need? (1 = not at all, 7 = completely) Does the MAS provide sufficient information? (1 = not at all, 7 = completely) Is the system accurate? (1 = not at all, 7 = completely) Are you satisfied with the accuracy of the MAS? (1 = not at all, 7 = completely) Do you think the output is presented in a useful format? (1 = not at all, 7 = completely) Is the information clear? (1 = not at all, 7 = completely) Do you get the information you need in time? (1 = not at all, 7 = completely) Does the system provide up-to-date information? (1 = not at all, 7 = completely) Please, rate your use of the MA information for the following purposes (1 = not at all, 7 = completely) Achieving lower cost of service or achieving lower costs in certain areas (personnel, pharmacy, purchasing of goods or services) Achieving higher efficiency or making certain services/procedures more cost efficient Offer value for patients and creating services or procedures to enhance efficacy Achieving higher patient satisfaction and quality of services
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User’s satisfaction
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MA Design
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“Hospital B makes relatively frequent changes in, and additions to, its set of services in order to offer value for patients. Its objectives are patient satisfaction, quality of services and creating services or procedures to enhance efficacy”
Use of MAS for decisionmaking control
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Fig. 1. The theoretical model Strategy
MA use (6)
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MA design (4)
Perfor mance (7)
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Org'l size (2)
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(1)
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Satisfaction with MA (5)
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Dashed line represents non hypothesized path.
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Region (3)
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Table 1. Results of CFA, CFA factors and variables correlations, and Cronbach’s alpha coefficients Standardized loadinga
Item reliabilit y
1. 2.
0.91 0.92
0.83 0.85
1. 2. 3.
0.85 0.90 0.84
0.72 0.81 0.71
1. 2. 3.
0.76 0.79 0.78
0.58 0.62 0.61
Factor
Item
0.91
0.83
0.91
0.77
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2. Satisfaction with MA
0.85
0.66
0.85
0.66
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3. MA Design
Average variance extracted
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1. Strategy
Composite reliability
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4. MA Use
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1. 0.82 0.67 2. 0.76 0.58 3. 0.73 0.53 Correlationb among factors, variables and Cronbach’s alpha coefficients 2. Satisfactio n with MA
1. Strategy
3. MA Design
4. MA Use
5. Size
6. Region
7. Perfor mance
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1. Strategy 0.89 2. Satisfaction with MA 0.71 0.95 3. MA Design 0.67 0.80 0.85 4. MA Use 0.55 0.46 0.67 0.80 5. Size -0.23 0.03 0.01 0.01 6. Region -0.01 -0.06 -0.13 -0.17 -0.18 7. Performance 0.04 0.10 0.12 0.20* -0.21* 0.18 a All standardized loadings are significant; b The correlations (1-4) among CFA factors above 0.20 are statistically significant. Diagonal elements are Cronbach’s alpha coefficients. Off-diagonal elements (5-7) are the correlations between the variables calculated in SPSS. * p < 0.05 (two-tailed). ** p < 0.01 (two-tailed). Table 2. Maximum likelihood estimates for full causal model (n=112) Independent Variable
Dependent Variable
Path
Strategy MA design Organisational size MA design Region MA design Strategy MA use Size MA use MA design MA use MA design Satisfaction with MA Satisfaction with MA MA use MA use Performance MA design Performance * p < 0.10, ** p < 0.05, *** p < 0.01
1-4 2-4 3-4 1-6 2-6 4-6 4-5 5-6 6-7 4-7
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Path Coefficients 0.59 *** -0.10 -0.08 0.22 *** -0.09 0.39 *** 0.51 *** 0.34 ** 0.22* 0.13
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Table 3. Maximum likelihood estimates for parsimonious causal model (n=112) Independent Variable Dependent Variable Path
0.62 *** 0.24 *** 0.42 *** 0.68 *** 0.40 ** 0.26*
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1-4 1-6 4-6 4-5 5-6 6-7
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Strategy MA design Strategy MA use MA design MA use MA design Satisfaction with MA Satisfaction with MA MA use MA use Performance * p < 0.10, ** p < 0.05, *** p < 0.01
Path Coefficients
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Figure 2. Significant path coefficients for the most parsimonious model
H4: .24***
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Strategy (1)
H1: .62 ***
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H11: .26 *
H7: .42 ***
MA Design (4)
MA use (6)
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Org'l size (2)
H10: .40**
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H8: . 68***
Performance (7)
Satisfaction with MA (5)
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* p < 0.10, ** p < 0.05, *** p < 0.01
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Region (3)
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S0168-8510(14)00084-0 http://dx.doi.org/doi:10.1016/j.healthpol.2014.03.011 HEAP 3203
To appear in:
Health Policy
Received date: Revised date: Accepted date:
28-7-2013 14-1-2014 18-3-2014
Please cite this article as: Macinati MS, Pessina EA, Management accounting use and financial performance in public health-care organisations. Evidence from the Italian National Health Service, Health Policy (2014), http://dx.doi.org/10.1016/j.healthpol.2014.03.011 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Management accounting use and financial performance in public health-care organisations. Evidence from the Italian National Health Service.
Management accounting use and financial performance
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in public health-care organisations.
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Evidence from the Italian National Health Service
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Manuela S. Macinati*
Eugenio Anessi Pessina
*Manuela S. Macinati, PhD (Corresponding author) Associate Professor
Università Cattolica del Sacro Cuore, Facoltà di Economia Largo F. Vito, 1 00168 ROMA Phone: 06.3015.5816
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Fax: 06.3015.4751 Email address: [email protected]
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Eugenio Anessi Pessina, PhD Università Cattolica del Sacro Cuore
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Facoltà di Economia
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Largo F. Vito, 1 00168 ROMA
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Phone: 06.3015.5816 Fax: 06.3015.4751
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Email address: [email protected]
Abstract: Reforms of the public health-care sector have emphasised the role of management accounting (MA). However, there is little systematic evidence on its use and benefits. To fill this gap, we proposed a contingency-based model which addresses three related issues, that is, whether: (i) MA use is influenced by contextual variables and MA design; (ii) topmanagement satisfaction with MA mediates the relationship between MA design and MA use; and (iii) financial performance is influenced by MA use. A questionnaire was mailed out to all Italian public health-care organisations. Structural Equation Modelling was performed to validate the research hypotheses. The response rate was 49%. Our findings suggest that: (i) cost-containment strategies encourage more sophisticated MA designs; (ii) MA use is directly and indirectly influenced by contingency, 2
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organisational, and behavioural variables; (iii) a weakly significant positive relationship exists between MA use and financial performance. These findings are relevant from the viewpoint of both top managers and policymakers. The former must make sure that MA is not only technically advanced, but also properly understood and along dimensions that may not fully translate into better financial results.
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Keywords: Contingency theory; MA use; MA design; performance; Italy
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appreciated by users. The latter need to be aware that MA may improve performance in ways and
1. Introduction
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Over the past decades, management accounting (MA) has increasingly gained importance within health-care organisations as a fundamental tool for the pursuit of efficiency and cost containment.
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For public health-care organisations, in particular, the adoption of MA has often been encouraged (or even required) by government policy, within the modernisation initiatives that have tried to
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reshape the public sector (New Public Management – NPM) [1,2]. Indeed, accounting innovations
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have been a fundamental component of these modernisation initiatives [2,3,4], since an association has commonly been assumed to exist between accounting information, improved
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decision-making and accountability [2] and, thereby, better organisational performance [5,6]. The NPM-inspired literature, however, has largely adopted either a normative stance – stating the recommended features and components of would-be reforms – or a descriptive one – presenting the specific features and components of actual reforms [7,8]. In this respect, MA and public health care are no exceptions. As a consequence, health-policy research has so far produced little systematic evidence on the actual use and benefits of MA in health-care organisations. Management accounting research, conversely, has produced some empirical evidence on such topics as the association between MA use and financial performance, the contextual determinants of MA use, and MA design [e.g. 9,10,11]. Most of this research has been carried out in the manufacturing context, but studies also exist that were conducted in a health-care setting [12-35]. These latter studies, in particular, do offer some meaningful contributions to both theorisation and current practice in the health-policy field. The evidence they provide, however, is still rather limited, 3
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generally circumscribed to individual variables viewed in isolation, and often inconclusive. Thus, hospital managers' use of MA has been found to contribute to financial performance [22]; MA effectiveness has been associated with contextual variables [e.g. 12-14,18,19,22,25,32]; technically refined MA systems have been found to help hospital managers cope with growing
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pressures for cost control [26,27,32]. According to other studies, conversely, MA has achieved limited success, mainly because its design failed to meet functional requirements or managerial
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needs [35]. Overall, the existing explanatory literature suggests that MA's impact on financial
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performance is affected by contextual variables (e.g. the organisation's strategic goals), MA’s own technical features (MA design), individual variables (e.g. individuals’ responses to MA practices),
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and the interactions thereof. The specific variables and relationships involved, however, have so far been insufficiently theorised and empirically investigated.
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In response to this research gap, and following Chenhall’s [36] call for more contingency-based research in service and non-profit organisations, this paper adopts a contingency approach and investigates the determinants and outcomes of MA use by public health-care managers. More
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specifically, the purpose of this paper is to propose and empirically test a comprehensive,
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contingency-based research model which addresses three related issues, that is, whether: (i) MA
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use is influenced by MA design and other contextual variables; (ii) top-management satisfaction with MA mediates the relationship between MA design and MA use; and (iii) financial performance is influenced by MA use.
Our definition of MA is drawn from the management accounting literature, where “MA refers to a collection of practices such as budgeting or product costing, while MAS [management accounting system] refers to the systematic use of MA to achieve some goal. MCS [management control system] is a broader term that encompasses MAS and also includes other controls such as personal or clan controls” [36, p. 129]. To test our model, we use data from the Italian National Health Service. The motivation for conducting this study in Italy is two-fold. On the one hand, the Italian health-care sector has undergone significant managerial reforms, although the impact of these initiatives on performance has been questioned [37,38]; within these reforms, MA has been presented as a tool that can 4
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enhance financial performance and improve efficiency. On the other hand, the strong decentralisation that has characterised the Italian National Health Service in the last two decades has produced enough variation in government policies and managerial practices to provide an excellent research setting for cross-sectional statistical analyses.
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In considering the effects of MA adoption, we focus on the financial dimension of health-care organisations' performance. In Italy and elsewhere, cost control has traditionally been a major
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health-policy goal. The current financial crisis, moreover, has further reinforced the emphasis on
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downsizing policies and austerity measures. Not surprisingly, financial results are often a key variable in evaluating top-management performance. Hence, although performance in health care
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– and particularly in publicly provided health care – obviously involves different perspectives, financial performance reflects the increasing emphasis on higher efficiency and cost containment
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and MA, with its focus on financial aspects, can potentially exert a pivotal role in reaching these objectives.
The paper’s intended contribution to the existing literature is two-fold.
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The first contribution is to health-policy research. As mentioned, the adoption of MA has often been
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encouraged by government policy, but its actual uses and benefits in health-care organisations are
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still largely unexplored. Insights into the causal paths linking context, MA, and organisational performance [39,40] would both extend existing knowledge and offer useful indications to healthcare managers and policy-makers.
The second contribution is to management-accounting research. As mentioned, management accounting research is largely focused on manufacturing. The peculiarities and complexities that characterise public health care, conversely, make it an ideal setting to study advanced topics of wider relevance for industries (namely professional services and other service industries) that are becoming increasingly important within most economies. As remarked by Abernethy and Lillis [25], moreover, health care provides a particularly suitable empirical setting in that specific structural arrangements and strategic orientations are both readily observable and recognised as having implications for other elements of control systems. In particular, the web of direct and indirect relationships linking contextual variables, MA, and financial performance, which this paper seeks to 5
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investigate, is a topic of wider relevance about which little empirical evidence has so far been collected. The paper is organised as follows. Section 2 presents a short description of the study's setting, that is, the Italian National Health Service. Section 3 provides the theoretical context for the study.
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Section 4 illustrates the research model and develops the research hypotheses. Section 5 is devoted to data and methods. Section 6 presents the empirical findings. Section 7 draws some
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conclusions. Section 8, finally, discusses the paper's research and policy implications.
2. The Italian National Health Service
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The Italian National Health Service (Servizio Sanitario Nazionale – SSN) covers the entire population, is tax-funded, and provides most care free of charge at point of service. It is a three-tier system with the Central Government at the top; 21 Regional Governments in the middle; and 265
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public health-care organisations1 at the bottom.
Since 1992, a series of reforms have been passed to introduce managerial principles and
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techniques, including a 2001 Constitutional amendment that significantly “regionalised” the SSN.
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The Regions currently define health policies; appoint public health-care organisations’ General
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Managers; provide them with goals and guidelines; fund their expenditures with regional taxes and user charges, with an equalisation fund to compensate for cross-regional differences in fiscal capacity. Individual public health-care organisations, in turn, have also gained greater autonomy, although with large cross-regional differences and a more recent, generalised tendency towards recentralisation at the regional level.
From an accounting perspective, public health-care organisations have traditionally relied on cashand commitment-based budgeting and reporting. Between 1992 and 2002, however, they gradually abandoned such bases to introduce accrual-based financial and management accounting. 1
Public health-care organisations, in turn, come in four types: (i) Local Health Authorities (Aziende Sanitarie Locali – Asl), each responsible for the health of the whole population in a given area and consequently acting partly as providers – through their own personnel, hospitals, and other facilities – and partly as commissioners; (ii) Hospital Trusts (Aziende Ospedaliere – AO), providing inpatient care and hospital-based outpatient care; (iii) Public Teaching Hospitals (Aziende Ospedaliero Universitarie – AOU), combining the services of a hospital with the education of medical students and consequently owned by or affiliated with a medical school; and (iv) Public Research Hospitals (Istituti di ricovero e cura a carattere scientifico - Irccs and Centri di ricerca), combining the services of a hospital with advanced medical research.
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Italian public health-care spending has traditionally been fairly low and still is (2,400 US$ PPP and 7.2% of GDP in 2012: OECD Health Data 2013). The deteriorating conditions of public finances, however, have emphasised the need for further cost containment policies. Following the 2001 Constitutional amendment, in particular, Regional Governments have been required to break even
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and have been subjected to constraints and sanctions if they fail to do so (e.g. an automatic increase in their own tax rates or a more general loss of autonomy, under a “financial recovery
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plan” supervised by the Central Government, in exchange for a partial bail-out). These constraints
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and sanctions, moreover, have become stronger and stronger over time. Individual public healthcare organisations, in turn, have similarly been expected to break even. The Regions in better
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financial conditions, conversely, have been able to claim further degrees of freedom from Central Government oversight. Financial results have thus been increasingly viewed as a key component
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of performance. MA use, in turn, has been increasingly perceived as pivotal in reaching these
3. Theoretical framework
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results.
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To explain the potential determinants of MA use in public health care and its outcomes, we rely on
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the contingency approach. The contingency approach is not a theory per se, but rather a general idea, “a framework for investigating identified factors for which we have a priori intuition based on other organizational, economic and sociological theories” [41, p.42; see 36 for a critical review]. Contingency-based research contends that an organisation’s structure is contingent upon contextual variables and that the different components of an organisation must “fit” with each other for the organisation to perform adequately [42]. The idea that performance depends on the fit between organisational context and structure is central to the contingency view. With specific respect to MA, the identification of the key contextual variables can be traced to the works of various organisational design researchers [43-46], which have subsequently found their way into the management control literature. Based on the premise of non-universality of management control systems, researchers have set out to investigate how different variables, such as the nature of the external environment as well as the organisation's 7
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structure, size, technology, and strategy, affect MA design [e.g. 11, 47-58]. The findings of these studies have been varied, but they generally support the existence of relationships between contextual variables and MA [see 36 for a review], although some of these relationships may be weak [59]. Accordingly, the basic premise of the contingency approach to MA is that MA (or, more
by the relevant organisation and this, in turn, affects performance [60].
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generally, any management control system) is affected by the particular set of circumstances faced
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Contingency-based accounting studies have generally assumed that “fit is the result of a natural
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selection process that ensures that only the best-performing organisations survive to be observed at any point of time” [61, p. 307]. In other words, when appraising fit, these studies do not examine
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whether the context-structure relationship affects performance, because the impact of fit (between management control systems and contingency factors) on effectiveness is assumed as intrinsic
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and only the best-performing organisations can survive. These studies, in other words, adopt a “congruency” theory application in that a simple unconditional association is predicted among variables [62,63].
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This congruency theory application, however, has been criticised because "signalling survival of
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the fittest is too crude a proxy for performance" [64]. It has consequently been suggested that
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contingency-based accounting research should employ organisational performance or other measures of effectiveness as the dependent variable [36]. Correspondingly, accounting researchers should analyse the "conditional association of two or more independent variables with a dependent outcome" [62, p. 514] and contingency models should be developed in order to ascertain the impact of the fit between context and structure on performance. The concept of outcome, in turn, is itself problematic. Although the outcome of MA has often been interpreted as organisational performance, contingency-based studies need to consider that the effects of MA on performance are “indirect and [are] conveyed to outcome criteria via some intervening constructs which links the variables” (65, p. 225-226). In particular, according to Chenhall [36, p. 135], contingency-based accounting studies should “first establish adoption and use of MCS, then [...] examine how they are used to enhance decision quality and finally
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investigate links with organisational performance”. This is the starting point for our model, which is presented in the next Section.
4. Model development and research hypotheses
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4.1 The model
The contingency-based model for our research is presented in Figure 1. It is a comprehensive
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model which includes: (i) multiple contingent variables; (ii) different aspects of MA that should be
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analysed following Chenhall [36]; and (iii) organisational performance as the dependent variable. In operationalising the variables, we adopted an intervening approach [36,62]. Specifically, we
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analysed the causal paths linking context, structure, and performance in order to identify the determinants of MA design and use and to explain the relationship between MA and performance
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through the direct and indirect effects of the intervening variables. Insert Figure 1 here
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The model involves three contingency variables (exogenous constructs). The variable “strategy”
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stems from conventional theories of organisational structure, referred to as the strategy-structure-
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performance paradigm. The variable “region” reflects the influence that Regional Governments exert on the adoption, design, and use of MA by individual health-care organisations, both indirectly (e.g. through the importance assigned to financial performance within regional policies) and directly (e.g. through guidelines on MA design and incentives for MA adoption). The variable "organisational size”, finally, was included for its reported contingent significance in several prior accounting studies [35,49,66].
The "heart" of the model includes several variables related to MA characteristics, mental models, and behaviours associated with MA, respectively labelled as "MA design", "satisfaction with MA", and "MA use", and modelled as endogenous constructs. The model assumes a relationship between MA and performance. The difficulties associated with measuring the influence of MA on performance, however, suggested employing a mediating variable, namely MA use, the omission of which would have “constitute(d) a blind spot in the 9
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framework” [67, p. 265]. The underpinning assumptions are that (i) MA cannot contribute to performance if it is not used and that (ii) its use, in turn, is influenced by individual satisfaction with the accounting system.
as previously discussed and consistent with [60, 68].
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The remainder of this Section presents the research hypotheses.
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The last element of the model is financial performance, which is viewed as the outcome variable,
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4.2. Contextual variables and MA design
Contingency-based accounting studies generally support the existence of a relationship between
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contextual variables and MA design, despite some weaknesses and fragmentary conclusions [59]. More specifically, the external environment in which organisations operate has been argued to
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affect MA design in terms of certain information characteristics [51,69-71]. This is because MA is intended to address decision-makers’ information needs, which are supposed to be influenced by the external environment. The literature (in general, but also with specific respect to health care
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[32]) highlights four critical intrinsic characteristics (or attributes, or scope) of accounting systems
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that are significant in assisting managerial decision-making and can consequently be used to
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describe MA design: (i) the level of detail provided; (ii) the ability to disaggregate costs according to behaviour; (iii) the frequency of information reporting; and (iv) the extent to which variances are calculated. In particular, we consider the following three links between the external environment (contingency variables) and MA design: (i) the link between strategy and MA design; (ii) the link between organisational size and MA design; (iii) the link between Regional policies and MA design.
- The link between strategy and MA design Contingency-based research contends that strategy influences MA design [e.g. 72,73]. In analysing the relationship between strategy and MA design, contingency-based accounting research highlights that certain designs are more consistent with certain strategies, since different strategies require different internal structures and processes, including appropriate MA information [e.g. 11,35,53,74-77]. In particular, organisations that emphasize cost strategies are supposed to 10
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require MA information that focuses on enhancing operating efficiencies and cost minimization (narrow scope of MA, [11]). Organisations that pursue differentiation strategies, on the contrary, mostly rely on external, future-oriented accounting information (broad scope of MA, [11]). With specific reference to health care, Pizzini [32] found that hospitals following a low-cost strategy need
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a more functional and sophisticated MA design because managers will require more articulated cost-oriented information to control costs [32,78]. On the other hand, hospitals following a
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differentiation strategy can be expected to focus their resources on clinical care to the detriment of
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MA sophistication. Similar results have been reported by Abernethy and Brownell [22] and by Boulianne [33].
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On the basis of the above discussion, we put forward the following hypothesis: H1: Strategy has a direct effect on the technical features of MA design (path 1-4), with cost-
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containment strategies encouraging MA sophistication.
- The link between organisational size and MA design
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Contingency-based accounting research has examined the role of organisational size in MA design
te
[e.g. 47,49,79], finding that size generally encourages MA sophistication, specialization, and use,
Ac ce p
for reasons of both motive and opportunity. In terms of motive, larger organisations are more complex and must cope with greater control issues. In terms of opportunity, they have access to greater resources and can benefit from economies of scale resulting from more functional and sophisticated MA designs. To some extent, these arguments have also been confirmed with specific reference to health-care organisations. Hill [24], for instance, claimed that larger hospitals will draw greater benefits from functional cost systems because they can spread the fixed costs of system development over more beds. Accordingly, the following hypothesis is proposed: H2: Organisational size has a direct effect on the technical features of MA design (path 2-4), with greater organizational size encouraging MA sophistication
- The link between Regional policies and MA design 11
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The institutional environment, which is characterized by the elaboration of rules, practices, symbols, beliefs, and normative requirements to which individual organisations must conform in order to receive support and legitimacy, can be expected to affect public hospitals' management control systems. Building on this theoretical premise, Abernethy and Chua [20] adopted a
ip t
contingency-based approach to analyse whether MA design in public health-care organisations is shaped by politics and stakeholder power. Their results demonstrate that the accounting control
cr
system is a function of the institutional environment’s pressures and that these pressures were
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exerted primarily through state funding agencies. Thus, there are theoretical and empirical reasons to believe that MA design in public health care can be contingent on the institutional environment
an
[see for example 20,23,29,36].
In Italy, as described in Section 2, jurisdiction over health care has been largely devolved to the 21
M
Regions. As a consequence, the performance objectives and management practices of individual health-care organisations will be strongly affected by Regional policies and guidelines. The Regional environment thus becomes an important context element for MA design. Particularly
d
relevant is the presence of Regions which, due to their critical financial performance, have been
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partially stripped of their autonomy and subjected to "financial recovery plans" under strict Central
Ac ce p
Government oversight. In these Regions, public health-care organisations have been pressured to invest in sophisticated MA designs in order to provide more detailed cost information to the Central and Regional governments and to satisfy stakeholder demands for efficiency. Accordingly, we posit that:
H3: Regional policies have a direct effect on the technical features of MA design (path 3-4), with financial recovery plans encouraging MA sophistication
4.3. MA use and its determinants According to Otley [80, p.122], the effectiveness of an organisation's MA system depends on “the appropriateness of its technical characteristics to the particular organisational and environmental circumstances”, but also on “the way in which organisational participants make use of the information that it provides”. 12
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Despite recognizing the importance of accounting and control systems use [61,80,81], the empirical literature has devoted little attention to its determinants [74]. We posit that the use of MA for decision-making depends directly or indirectly on a number of variables including contextual,
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technical, and individual-level variables.
- The links between contextual variables and MA use
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Contextual variables can exert a direct influence on the use of MA information. The management
us
accounting literature, in particular, suggests the presence of a direct link between strategy and MA use. For example, Chenhall and Langfield-Smith [72] found that the use of management
an
accounting systems varies according to the strategy pursued. Health-care organisations pursuing cost-based strategies can consequently be expected to make a more intensive use of MA
M
information in order to monitor and contain costs.
In addition to the direct effect of strategy on MA use, we expect that MA design intervenes in the relationship between strategy and MA use. As already stated, different strategies can be expected
d
to affect the configuration of MA and of the wider management control system, in order to provide
te
decision-makers with the information they need. With specific respect to health care, for instance,
Ac ce p
Kettelhut [82] and Hill [24] found that hospitals operating in markets with strong competition and/or significant penetration from managed-care organisations produced more extensive and detailed cost information and used these information in response to greater external pressures to control costs. Therefore, in addition to the direct effect of strategy on MA use, we posit that strategy affects MA design and this, in turn, affect the use of MA . Hence, the following research hypotheses are suggested: H4: Strategy has a direct effect on MA use (path 1-6), with cost-containment strategies encouraging MA use H5: MA design mediates the relationship between strategy and MA use (path 1-4-6)
In addition, as organisations become larger, the need for managers to handle great quantities of information increases to a point where they have to institute rules and other controls [79], not least 13
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because size generally implies complexity. The larger the organisation, therefore, the greater the reliance on formal controls, including an emphasis on MA information to assist in making and implementing decisions. Thus, we can expect a positive relationship between organisational size and the extent of MA use. Hence, we posit that:
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H6: Organizational size has a direct and positive effect on MA use (path 2-6)
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- The links between MA design, top-management satisfaction with MA, and MA use
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Both MA design and management satisfaction with the information that MA provides can influence MA use.
an
On the one hand, the technical features of MA design will affect its ability to provide decisionmakers with the information they need and, thus, MA use. To put it differently, if MA design is
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technically inadequate, the information that MA provides will not be used, because it will be perceived as unable to support managerial decision-making. With respect to health care, in particular, the literature has strongly suggested the use of highly refined cost systems to help
d
hospital managers respond to growing pressures for cost control [19,32].
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Thus, the following hypothesis is developed:
Ac ce p
H7: MA design has a direct and positive effect on MA use (path 4-6)
At the same time, MA effectiveness in supporting decision-making has been shown to depend not only on the technical features of MA design, but also on MA's coherence with managers’ mental models [83]. Management satisfaction with MA must consequently be viewed as an another important determinant of MA use. User satisfaction is the “extent to which users believe that the information system available to them meets their information requirements” [84]. User satisfaction includes an affective response towards the delivery of information [84,85] in that it reflects the user’s feelings about the information system’s usefulness [86]. Based on these premises, we expect user satisfaction to be influenced by the technical features of MA design and, in turn, to influence MA use. In addition, we posit that user satisfaction mediates the relationship between MA design and MA use. More specifically, if managers perceive that the information provided by their 14
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MA system meets their information requirements, they will be satisfied with it, and will consequently be more likely to use it for decision-making and control purposes [86,87,88]. Accordingly, we posit the following hypotheses: H8: MA design has a direct and positive effect on satisfaction with MA (path 4-5)
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H9: Satisfaction with MA mediates the relationship between MA design and MA use (path 4-5-6)
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H10: Satisfaction with MA has a direct and positive effect on MA use (path 5-6)
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4.4 MA use and performance
The ultimate purpose of MA implementation is to improve organisational performance, including
an
financial performance. However, there is little empirical evidence on the positive relationship between MA characteristics and financial performance, also because a large portion of MA benefits
M
is generally qualitative and intangible [89].
To a large extent, the impact of MA on performance will depend on the way in which organisational participants make use of the information they receive [90-93], so much so that “the use of control
d
information can be more significant than the formal design of the control system” [67, p.274]. In
Ac ce p
performance.
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addition, MA use can also be expected to act as a mediating variable linking MA design to
Following our choice to focus on financial performance, the following hypotheses are consequently suggested:
H11: MA use has a direct positive effect on financial performance (path 6-7)
H12: MA use mediates the relationship between MA design and financial performance (path 4-6-7)
5. Methods 5.1 Data
To test the hypotheses, questionnaires were sent personally to the General Managers of all Italian public health-care organisations (n=265). Personalizing the survey was intended to increase the response rate [94,95].
15
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Consistent with the research framework, the questionnaire (see Appendix 1) was made up of four Sections addressing: (i) strategy, (ii) MA design, (iii) top-management satisfaction with MA, and (iv) MA use for decision-making. The questionnaire also included a cover letter explaining the purpose of the study and a preliminary Section intended to collect data on the respondents and their
ip t
organisations. Geographic location (Region), size, and financial performance were not addressed in the questionnaire as they could be gathered from official sources. A recall to the General
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Managers who had not answered within three weeks was then conducted using a combination of
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mail, email, and telephone [73].
A total of 131 questionnaires were returned, with a response rate of 49%. This response rate is
an
similar to those reported in other management accounting surveys [e.g. 90,96]. In addition, it complies with Baruch's [97] recommendations in that Baruch reported an average (standard
M
deviation) response rate for surveys of top managers of 35.5% (13.3%). Nevertheless, two sets of tests were conducted to rule out the presence of non-response bias. First, following Oppenheim [98, p.34], a comparison was performed between the mean scores of
d
early and late responses. To this end, respondents were divided in two halves based on the date of
te
receipt of the completed questionnaire; t-tests were then performed on the continuous variables
Ac ce p
included in the questionnaire (strategy, MA design, top-management satisfaction with MA, and MA use for decision-making). No statistically significant differences were found between the mean scores of the two halves.
Second, the sample was analysed with reference to the main stratum variables: geographic location (North, Centre, South), organisational type (see footnote 1), hospital size (total operating revenues, see par. 5.2), and financial performance (operating expenses, see par. 5.2). Chi-square tests did not find any statistically significant differences between the respondents and the entire population in terms of either geographic location (! 2= 4.5, p = .13) or organisational type (! 2= 1.28, p = .52 ). Similarly, t-tests did not find any statistically significant differences between the respondents and the entire population in terms of hospital size (t = -.009; p = .99), and financial performance (t = .83; p = .41).
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Among responding organisations, operating revenues averaged m€ 388.55 (SD: 294.16). 41.4% were located in a Region under a financial recovery plan. The mean age of respondents was 53 years. The respondents had held their current positions for an average of 3.4 years. Roughly 40%
5.2 Measures
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The measures employed in the empirical analysis are described below.
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of the respondents had a background in medicine; 10% were female2.
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Strategy. Following previous approaches to strategy measurement in health care [e.g. 25, 99,100], we employed the measure developed by Miles and Snow [77]. Miles and Snow developed this
an
instrument to assess an organisation’s overall strategic orientation. To this end, respondents were asked to indicate the degree of emphasis that their firms had given to prospector-type and
M
defender-type strategic priorities. Consistent with Abernethy and Lillis [25], we used Miles and Snow's measure not to ascertain whether a health-care organisation fits into the “prospector” or “defender” classification, but rather to assess the degree to which it is committed to quality service
d
or efficiency/cost containment strategies. Thus, our questionnaire presented health-care managers
te
with a brief profile of each strategy and asked them to rate, on a seven-point Likert scale, how well
Ac ce p
each profile described their organisations.
Organisational size. In health care, size is often proxied by the number of hospital beds or admissions. Italian public health-care organisations (especially ASLs, see footnote 1), however, also perform significant public-health and outpatient activities. Size was thus measured by the total annual operating revenues of each health-care organisation. Region. Regional features and policies were summarized by a dummy variable for whether the Region was subject to a financial recovery plan. MA design. MA design was measured according to the four "attributes" identified in Section 4: (i) level of detail provided; (ii) ability to disaggregate costs according to behaviour; (iii) frequency of
2
A correlation analysis of the respondents’ demographic variables with the variables employed in the questionnaire was performed with the aim to detect potential spurious effects. No significant associations were observed. In performing the correlation analysis we considered the type of the variables used (if they were continuous or discrete).
17
Page 17 of 39
information reporting; and (iv) extent to which variances are calculated [see 32]. For each attribute, respondents were asked to assess their MA systems over a seven-point Likert scale. Top management satisfaction with MA. Doll and Torkzadeh [87] identified five components of user satisfaction with information systems: content, accuracy, format, ease of use, and timeliness.
ip t
For each component, they also identified a number of specific items. These items were slightly adapted to better fit the purpose and context of our study3. For each item, respondents were asked
cr
to express their satisfaction using a seven-point Likert scale.
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Use of MA. Despite its importance, the concept of “MA use” has not been well developed in the management accounting literature. In order to investigate the extent to which General Managers
an
use MA information for specific decision-making and control purposes, four questions were constructed. For each question, respondents were asked to rate their use of MA over a seven-point
M
Likert scale.
Performance. Performance is a multi-dimensional concept, whose attributes change over time as well as across stakeholders and organisations. In public organisations, defining and measuring
d
performance is even more complex, because stakeholder expectations are heterogeneous, cover
te
multiple issues, often produce a wide range of positions on each issue, shift rapidly over time, and
Ac ce p
are difficult to specify and prioritise. The introduction of MA, however, has generally been expected to improve the financial conditions of public health-care organisations, not because public hospitals should pursue profit as their ultimate goal, but rather because financial viability is a prerequisite for the provision of adequate patient care. Improved financial performance can thus be viewed as a key outcome of MA adoption by public health-care organisations. In this study, financial performance was expressed in terms of operating expenses scaled by total operating revenues.
5.3 Statistical analysis The data were investigated by means of confirmatory factor analysis (CFA) and structural equation modelling (SEM). According to the two-step approach recommended by Anderson and Gerbing [101], in particular, CFA was employed to assess the adequacy of the measurement model, while 3
In particular, the questions “Is the system user friendly?” and “Is the system easy to use?” were omitted, as they did not appear to be particularly useful in assessing General Managers’ satisfaction with MA.
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SEM was subsequently used to test the research hypotheses by aggregating the items reflecting a common construct (mean values of the variables). Before performing CFA and SEM, the data set was verified for compliance with the main assumptions underlying these techniques [102]. Since the data were found to moderately deviate
ip t
from a normal distribution, in particular, robust maximum likelihood estimation was used in both CFA and SEM [103]. A similar approach was used by Castañeda et al [104] and is recommended
us
cr
by Curran et al. [105].
6. Results
an
6.1. Confirmatory factor analysis
Initially, a CFA model was evaluated using all the items in the questionnaire. However, the CFA
M
model fit indices did not fully meet the cut-off values recommended by the most recent literature. Presumably, this was because a model composed of many parameters will often show computational problems, poorer fit, and increased measurement errors, especially when the
d
sample size is small or moderate [106]. These issues can be tackled using partial disaggregation
te
models [107]. The aim of partial disaggregation procedures4 is to reduce the number of observed
Ac ce p
variables and parameters included in CFA models [for a complete discussion see, for example, 108,109].
Using partial disaggregation5, CFA results showed a Satorra-Bentler chi-square statistic of 50, returning a significant p-value. Bagozzi and Yi [110], however, noted that chi-square is very sensitive to sample size. Marsh et al. [111], moreover, criticised the relevance of chi-square statistics for model evaluation and suggested the use of other goodness-of-fit measures. Among these, the chi-square to degrees of freedom ratio was 1.3 (df: 38). CFA fit indices were greater than the recommended value of 0.95 (NNFI=0.97; CFI=0.98; IFI=0.98; GFI=0.96). RMSEA and SRMR were both 0.05, showing an adequate model fit [83,84,85].
Partial disaggregation procedures use items aggregated randomly to form three indicators per construct. Some of the variables considered in the model were defined using only one item. These were excluded from CFA.
4 5
19
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Table 1 presents the robust maximum likelihood standardized loadings, the item reliabilities, the derivative statistics of composite reliability, and the average variance extracted (AVE), as well as the correlations among the CFA factors and Cronbach's alpha coefficients. Table 1 also reports the correlations between the other variables included in the model.
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Insert Table 1 here
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The results summarised in Table 1 were used to confirm the measurement model's reliability,
us
convergent validity, and discriminant validity.
Reliability was assessed at two levels: item reliability and construct reliability. Single-item reliability,
an
which refers to the amount of variance in an item due to underlying construct rather than to error, was always greater than 0.50, thus supporting item reliability. Construct reliability, which refers to
M
the degree to which an instrument reflects an underlying factor, was assessed by composite reliability. Composite reliability was greater than the recommended value of 0.70 for each and so was Cronbach's alpha, thus supporting construct reliability. Having ensured that the scales meet
d
the necessary levels of reliability, scale validity was assessed. To this end, convergent and
te
discriminant validity were tested. Convergent validity, which assesses the degree to which
Ac ce p
dimensional measures of the same concept are correlated, was measured by the Average Variance Extracted (AVE). AVE values were greater than 0.5 thus demonstrating that convergent validity was not an issue. Discriminant validity, which is the degree to which conceptually similar concepts are distinct, was assessed by comparing the AVE with the maximal squared correlation of CFA factors (Table 1, correlations 1-4) [112]. In particular, the maximal squared correlation of CFA factors (0.64) was below the minimal AVE (0.66), thus satisfying the discriminant validity criterion of Fornell and Larker [113].
Finally, procedural and statistical arrangements were employed to minimize the occurrence of common method bias (CMB) [114]. The procedural arrangements were related to the design of the questionnaire, while the statistical arrangements included Harman’s single-factor test, which was conducted by performing exploratory factor analysis (EFA) on all the items of the study. The examination of the unrotated factor structure revealed four factors with eigenvalues above one, 20
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with no single dominant factor explaining a majority of the variance [114]. Therefore, CMB did not appear to be a problem for this study.
6.2. Structural equation model
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SEM analysis was carried out in three main steps.
In the first step, the full theoretical model shown in Figure 1 was tested, imposing the causal
cr
structure of the hypothesised model on the set of observed data. The Satorra-Bentler chi-square
us
statistic was insignificant (9.7, p=0.20), the chi-square to degrees of freedom ratio was 1.38 (df: 7), and the fit indices (NNFI=0.96; CFI=0.98; IFI=0.99; GFI=0.98; RMSEA=0.05; SRMR=0.04) showed
an
that the structural model fitted the data. Table 2 presents the standardized path coefficients and their statistical significance levels for the full causal model6. Six of the ten causal paths specified in
M
the full model were found to be statistically significant, although to different extents, with positive path coefficients: (i) strategy and MA design; (ii) strategy and MA use; (iii) MA design and MA use;
performance.
d
(iv) MA design and satisfaction with MA; (v) satisfaction with MA and MA use; and (vi) MA use and
te
Insert Table 2 here
Ac ce p
In the second step, an additional confirmatory post ad hoc analysis was performed using nested models in order to identify the most parsimonious model [101]. The final structural model shown in Fig. 2 is the most parsimonious and excludes the non-significant structural paths from the initial full causal model. In the final model, the Satorra-Bentler chi-square statistic remained insignificant (15.26, p=0.10), the chi-square to degrees of freedom ratio was 1.76 (df: 13), and the values of the fit indices (NNFI=0.97; CFI=0.99; IFI=0,99; GFI=0.98; RMSEA=0.03; SRMR= 0.04) showed a good fit to the data. The chi-square difference between the two models was not significant (Δχ2(4) =5.56); the AIC (Akaike Information Criterion) value in the final model was 51, compared to 53 in the full causal model; the final model thus represents the best fit to the data overall. Under the final model, the list of statistically significant paths did not change from the full initial model, nor changed the
6
Although no hypothesis was developed about the relationship between MA design and performance, the related path was added to test the MA design-performance link via the indirect effect of MA use.
21
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signs of their standardized coefficients (Table 3). Hence, hypotheses H1, H4, H7, H8, H10 and H11 were supported. Insert Figure 2 here Insert Table 3 here
ip t
In the third and final step, an analysis was conducted on standardized direct, indirect, and total effects in order to test hypotheses H5, H9, H12. The indirect effects were obtained via Lisrel output
cr
using the product of coefficients method. The significance of indirect effects was determined with
us
PRODCLIN software using the M-test for asymmetric confidence intervals [115]. Results showed that the path between MA design and MA use via the indirect effect of Satisfaction with MA was
an
significant (indirect effect = 0.27). Similarly, results showed the significance of the indirect effect of MA design in the relationship between Strategy and MA use (indirect effect = 0.26). Both
M
hypotheses H5 and H9 were thus supported. In contrast, H12 was not supported since the indirect effect of MA use in the relationship between MA design and Performance was not significant (indirect effect = 0.11).
te
d
Insert Table 4 here
Ac ce p
7. Discussion and conclusions
Research on MA in the public health-care sector has often taken a normative or a descriptive stance, without a strong and clear reference to theory. The existing empirical evidence on the use and benefits of MA, therefore, is still rather limited, generally circumscribed to individual variables viewed in isolation, and often inconclusive. Consistent with Chenhall’s [36] call for more contingency-based research in service and nonprofit organisations, the purpose of this paper was to partially fill this gap by investigating the complex web of relationships that link contextual variables, MA’s technical features, MA use, individual-level variables, and organisational performance, so as to identify both the determinants of MA use and its effects on performance. To this end, we developed a contingency-based theoretical model and tested it using data on MA practices in Italian public health-care organisations.
22
Page 22 of 39
More specifically, our model was intended to test three sets of relationships: (i) the impact of three contingent variables (strategy, size, and Regional context) on MA design; (ii) the impact of MA design on MA use by health-care managers, be this impact direct or mediated by manager satisfaction with their organisation's MA, as well as the relationship between strategy and MA use
ip t
via MA design; and (iii) the direct relationship between MA use and financial performance, as well as the relationship between MA design and financial performance as mediated by MA use.
cr
With respect to the first issue (impact of strategy, size, and Regional context on MA design), only
us
strategy was found to matter. Consistent with research carried out in the private sector and with the results obtained by Pizzini [32] for US hospitals, cost-containment strategies were found to
an
encourage more sophisticated MA designs, probably because public health-care managers require more information for cost control purposes. This finding suggests that MA adoption by hospitals
M
cannot be viewed as a merely ceremonial process [17]. On the contrary, hospitals seem to accept that MA can support the pursuit of strategies and to consciously invest on MA design when cost containment becomes their priority. Interestingly, no association was found between organisational
d
size and MA design, possibly because Italian public health-care organisations are all fairly large
te
and must consequently cope with comparable decision-making and control issues. Similarly, no
Ac ce p
association was found between the relevant Region being subject to financial recovery plans and MA design, hopefully because financial recovery plans have forced the "weakest" Regions to invest in management tools and to partially catch up with the "best performers", at least in this regard.
With respect to the second issue (the relationship between MA design and MA use, be it direct or mediated by managers' satisfaction with MA), both direct and indirect impacts were found to be positive and statistically significant. In addition, MA use was also found to be encouraged by the pursuit of cost-containment strategies both directly or indirectly via the mediating role of MA design. Thus, contingency, organisational, and behavioural variables all seemingly come into play and complement one another to influence MA use. Interestingly, satisfaction with MA is strongly and directly influenced by MA design. Since satisfaction with MA can be considered a subjective measure of information system success in organisations [86], this result suggests that higher MA 23
Page 23 of 39
sophistication can influence the perceived effectiveness of MA, although MA use will also depend upon the extent to which the health-care organisation focuses on cost-containment strategies. Finally, with respect to the third issue (the impact of MA design and use on financial performance), no statistical significance was found for the direct and indirect relationships between MA design
ip t
and financial performance. Conversely, a positive relationship was found between MA use and
us
not MA design per se that influences performance, but its use.
cr
financial performance, although with weak statistical significance. These results confirm that it is
8. Implications
an
The idea that the adoption of private-sector practices and techniques by public-sector organisations, per se, cannot be expected to improve performance, is not entirely new. In the
M
existing literature, however, this result has often been attributed to a merely ceremonial introduction of management techniques [19]. We add to this literature and to management accounting research by: (i) suggesting the existence of a joint effect of contingency, organisational,
d
and behavioural variables on MA use, and (ii) providing modest evidence of a positive relationship
te
between MA use and financial performance.
Ac ce p
These results are relevant from the viewpoint of both managers and policymakers. From a managerial perspective, these results suggest that, to avoid a merely ceremonial introduction of MA, MA use should be encouraged through a two-pronged approach: (i) develop a technically sound MA system, but also (ii) make sure that managers appreciate its qualities and learn to fully exploit its potential.
From a policy viewpoint, this study provides policymakers with two meaningful indications. First, preventing a merely ceremonial adoption of MA is also a matter of policy. According to our findings, when efficiency and cost containment become a real priority, as opposed to being a purely rhetorical goal, MA design and use are both significantly and positively affected. For efficiency and cost containment to be a real priority, however, policymakers need to design appropriate incentives in terms, for instance, of funding criteria for individual public health-care organisations and reward systems for their General Managers. Given the importance of effectiveness and equity in publicly 24
Page 24 of 39
funded health care, however, this is a rather complex task, the obvious risks being to excessively encourage cost containment at the expense of service quality [31] and to further widen the gap between the best and the worst performing organisations by systematically rewarding the former and penalising the latter. Second, to the extent that efficiency and cost containment are indeed a
ip t
priority, national and regional policies that encourage MA adoption find at least some support in our findings in that MA use has been shown to positively affect financial performance. Admittedly, the
cr
statistical significance of the relationship between MA use and financial performance is weak, but
us
this is not particularly surprising. In general, as mentioned in Section 4, there is little empirical evidence of the positive relationship between MA characteristics and financial performance,
an
because a large portion of MA benefits is qualitative and intangible. With specific respect to public and non-profit organisations, moreover, efficiency gains will generally be used not to increase net
M
income, but rather to improve service quantity and quality, unless (as is the case for many Italian health-care organisations) financial conditions become so critical that improving net income (i.e., reducing deficits) is indeed a key priority. In other words, MA use may reasonably be expected to
te
translate into better financial results.
d
improve organisational performance in ways and along dimensions that do not meaningfully
Ac ce p
Our focus on financial performance - and the resulting exclusion from the model of variables that capture effectiveness-oriented initiatives - indeed represents the main limitation of this study. Future research could include these variables and focus on longitudinal studies in order to observe causal linkages between variables over longer periods of time. Despite these limitations, this study has improved our understanding of MA use, its determinants and its effects; it has also shed some light on the impact of reforms and policies currently under implementation in health care.
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Appendix Research areas
Variables
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Please, place healthcare organization along a seven-point scale 1 = not at all, 7 = completely “Hospital A believes that doing the best job possible in its existing range of services. Its objectives are achieving lower costs, achieving lower costs for specific inputs (personnel, pharmaceuticals …) and achieving higher efficiency”
To what extent does the cost accounting system provide data that allow you to analyze costs 1 = not at all, 7 = completely The cost accounting function can easily customize reports to the specification of users? 1 = strongly agree, 7 = strongly disagree Does your cost system have a formalized method of distinguishing costs according to their behaviour? 1 = not at all, 7 = completely How often does the cost accounting system report information? 1=rarely, 7=frequently To what extent does your cost system provide data that allow you to analyse variances? 1 = not at all, 7 = completely Does the MAS provide the precise information you need? (1 = not at all, 7 = completely) Does the information content meet your needs? (1 = not at all, 7 = completely) Does the MAS provide reports that seem to be just about exactly what you need? (1 = not at all, 7 = completely) Does the MAS provide sufficient information? (1 = not at all, 7 = completely) Is the system accurate? (1 = not at all, 7 = completely) Are you satisfied with the accuracy of the MAS? (1 = not at all, 7 = completely) Do you think the output is presented in a useful format? (1 = not at all, 7 = completely) Is the information clear? (1 = not at all, 7 = completely) Do you get the information you need in time? (1 = not at all, 7 = completely) Does the system provide up-to-date information? (1 = not at all, 7 = completely) Please, rate your use of the MA information for the following purposes (1 = not at all, 7 = completely) Achieving lower cost of service or achieving lower costs in certain areas (personnel, pharmacy, purchasing of goods or services) Achieving higher efficiency or making certain services/procedures more cost efficient Offer value for patients and creating services or procedures to enhance efficacy Achieving higher patient satisfaction and quality of services
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User’s satisfaction
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MA Design
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“Hospital B makes relatively frequent changes in, and additions to, its set of services in order to offer value for patients. Its objectives are patient satisfaction, quality of services and creating services or procedures to enhance efficacy”
Use of MAS for decisionmaking control
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Fig. 1. The theoretical model Strategy
MA use (6)
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MA design (4)
Perfor mance (7)
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Org'l size (2)
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(1)
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Satisfaction with MA (5)
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Dashed line represents non hypothesized path.
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Region (3)
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Table 1. Results of CFA, CFA factors and variables correlations, and Cronbach’s alpha coefficients Standardized loadinga
Item reliabilit y
1. 2.
0.91 0.92
0.83 0.85
1. 2. 3.
0.85 0.90 0.84
0.72 0.81 0.71
1. 2. 3.
0.76 0.79 0.78
0.58 0.62 0.61
Factor
Item
0.91
0.83
0.91
0.77
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2. Satisfaction with MA
0.85
0.66
0.85
0.66
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3. MA Design
Average variance extracted
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1. Strategy
Composite reliability
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4. MA Use
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1. 0.82 0.67 2. 0.76 0.58 3. 0.73 0.53 Correlationb among factors, variables and Cronbach’s alpha coefficients 2. Satisfactio n with MA
1. Strategy
3. MA Design
4. MA Use
5. Size
6. Region
7. Perfor mance
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1. Strategy 0.89 2. Satisfaction with MA 0.71 0.95 3. MA Design 0.67 0.80 0.85 4. MA Use 0.55 0.46 0.67 0.80 5. Size -0.23 0.03 0.01 0.01 6. Region -0.01 -0.06 -0.13 -0.17 -0.18 7. Performance 0.04 0.10 0.12 0.20* -0.21* 0.18 a All standardized loadings are significant; b The correlations (1-4) among CFA factors above 0.20 are statistically significant. Diagonal elements are Cronbach’s alpha coefficients. Off-diagonal elements (5-7) are the correlations between the variables calculated in SPSS. * p < 0.05 (two-tailed). ** p < 0.01 (two-tailed). Table 2. Maximum likelihood estimates for full causal model (n=112) Independent Variable
Dependent Variable
Path
Strategy MA design Organisational size MA design Region MA design Strategy MA use Size MA use MA design MA use MA design Satisfaction with MA Satisfaction with MA MA use MA use Performance MA design Performance * p < 0.10, ** p < 0.05, *** p < 0.01
1-4 2-4 3-4 1-6 2-6 4-6 4-5 5-6 6-7 4-7
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Path Coefficients 0.59 *** -0.10 -0.08 0.22 *** -0.09 0.39 *** 0.51 *** 0.34 ** 0.22* 0.13
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Table 3. Maximum likelihood estimates for parsimonious causal model (n=112) Independent Variable Dependent Variable Path
0.62 *** 0.24 *** 0.42 *** 0.68 *** 0.40 ** 0.26*
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1-4 1-6 4-6 4-5 5-6 6-7
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te
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M
an
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Strategy MA design Strategy MA use MA design MA use MA design Satisfaction with MA Satisfaction with MA MA use MA use Performance * p < 0.10, ** p < 0.05, *** p < 0.01
Path Coefficients
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Figure 2. Significant path coefficients for the most parsimonious model
H4: .24***
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Strategy (1)
H1: .62 ***
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L
H11: .26 *
H7: .42 ***
MA Design (4)
MA use (6)
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Org'l size (2)
H10: .40**
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H8: . 68***
Performance (7)
Satisfaction with MA (5)
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* p < 0.10, ** p < 0.05, *** p < 0.01
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Region (3)
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