Pacific Accounting ReviewPerformance measurement in Indonesia: the case of local governmentRusdi Akbar Robyn Pilcher Brian Perrin
Article information:To cite this document:Rusdi Akbar Robyn Pilcher Brian Perrin, (2012),"Performance measurement in Indonesia: the case of localgovernment", Pacific Accounting Review, Vol. 24 Iss 3 pp. 262 - 291Permanent link to this document:http://dx.doi.org/10.1108/01140581211283878
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Performance measurementin Indonesia: the case of local
governmentRusdi Akbar
Fakultas Ekonomi, Universitas Gadjah Mada, Yogyakarta, Indonesia, and
Robyn Pilcher and Brian PerrinSchool of Accounting, Curtin University, Perth, Australia
Abstract
Purpose – The purpose of this paper is to investigate the implementation of performancemeasurement systems (PMSs) in Indonesian local government (ILG) using Smart PLS. Couched withinan institutional theory framework, it explores a conceptual model developed to explain the hypothesisedrelationships between technical and organisational factors and the development and use of performanceindicators and accountability practices.
Design/methodology/approach – Surveys were sent to senior finance officers in all localgovernments (457) across Indonesia with a response rate of 21.4 percent being achieved. Smart PLSwas used to assess the quality of the data and analyse the research model proposed.
Findings – Findings revealed that ILGs developed performance indicators more to fulfil regulatoryrequirements than to make their organisation more effective and efficient. As a way of increasing thesuccess of PMS implementation management commitment through good leadership was found to be amajor contributor. Coercive pressure from central government impacted on the result as did normativeisomorphism by way of widespread training by universities (and others) and the subsequent sharingof this knowledge.
Practical implications – The findings will assist Indonesian central government formulate futuregovernment policy as well as design appropriate strategies for implementing the second wave of(bureaucratic) reform.
Originality/value – Set in a local government environment in a developing country, this research isoriginal and makes three major contributions. First, it provides an understanding of factors influencingthe development and use of performance measures in the ILG context. Second, the use of Smart PLS isoriginal in this context and fills a gap in the literature examining local government PMS. Last,the existence of institutional isomorphism reaffirms that this theory is still applicable in the twenty-firstcentury and relevant as an explanator of the results in the context examined here.
Keywords Performance measurement systems, Indonesia, Local government, Institutional theory,Isomorphism, PLS analysis, Performance management
Paper type Research paper
1. IntroductionMany government entities in developed countries have introduced elements of newpublic management (NPM)[1] (Hood, 1991, 1995; ter Bogt, 2004) which is based ona fundamental concept that public sector organizations can, and even should, borrow
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The authors would like to acknowledge the anonymous reviewers at the AFAANZ 2010Conference for their feedback on an earlier version of the paper. The authors would also like tothank the two anonymous reviewers who provided feedback as part of this journal’s reviewprocess.
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many management strategies from the private sector. In Indonesia the governmentintroduced performance measurement reporting to respond to public demand onproductivity, transparency and accountability. According to Cheung (2011, p. 131),the NPM and good governance models were the two “dominant paradigms” havingthe “greatest impact on Asian (in which he includes Indonesia) institutional reforms”.
This study focuses on two pivotal aspects in the public sector – accountability andperformance measurement. Over the last 40 years the idea of performance measurementhas been the focus of considerable attention from both academics and practitioners(Neely, 1999; Kihn, 2010). Initially, the research in the field mainly concentrated onperformance measurement in the private sector (Kaplan, 1983; Johnson and Kaplan,1987; Chenhall and Smith, 2007). However, since then there have been a number ofstudies addressing the issues of performance measurement in the public sector(Hood et al., 1998; Cavalluzzo and Ittner, 2004; Micheli and Neely, 2010). In Indonesia, theinterest in performance measurement began to emerge at the beginning of the reform erain 1999 when President B.J. Habibie signed a presidential instruction (Inpres No. 7/1999),the Performance Accountability Report of State Apparatus (known as LAKIP).
Coinciding with the first wave of public sector reform, this research investigates theimplementation of performance measurement systems (PMS) in Indonesian localgovernment (ILG). A second generation structural equation modelling technique knownas partial least squares (PLS) was used to analyse the proposed model and relationships.Based on a survey of ILGs, the research explores a conceptual model adaptedand developed to explain the hypothesised relationships between technical andorganisational factors and the development and use of performance indicatorsand accountability practices. The theoretical development and interpretation of thisresearch is drawn from institutional theory. A major contribution of this research is thatit provides an understanding of factors influencing the development and use ofperformance measures which, in turn, could be used to formulate future governmentpolicy. Further, it fills a gap in the literature exploring PMS and accountability in adeveloping country – in this case, Indonesia. This paper begins with a brief literaturereview followed by an explanation of the theoretical framework employed. Section 4then considers the research model and hypotheses development, and Section 5 discussesthe research method used. Section 6 presents the results of the research using SmartPLS,with these results discussed in the penultimate section. A conclusion and suggestions forfuture research ends this paper.
2. Literature reviewNPM and accountabilityNPM was introduced in Europe in the 1980s. Lapsley and Pallot (2000) considered thisframework separately from that of institutional theory, whereas Bovaird and Downe(2006) use institutional isomorphism to understand NPM-type reforms. This paperadopts the latter framework as it considers whether, with the introduction of PMS,institutional isomorphism – particularly coercive – plays a role in the implementationprocesses adopted by ILG.
The development of NPM was seen as a means by which to enhance accountabilityand transparency of governments and this, in turn, required performance informationthat was more comparable, relevant and useful for decision-making within the publicsector. Romzek and Dubnick (1998, p. 6), define accountability as “a relationship in which
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an individual or an agency is held to answer for performance that involves somedelegation of authority to act.” Government organisations are created by the public,for the public, and need to be accountable to the public. Given the myriad definitions andvariations on the term “accountability”, for the purposes of this paper, accountability isseparated into two components – internal accountability (the accountability ofmanagement to the major/head of district (elected official)), and external accountability(accountability of ILG to its stakeholders such as central government, parliamentsand citizens).
Performance measurement/PMSManaging and measuring performance has been one of the key drivers in the reform ofthe public sector (Gianakis, 2002). Osborne and Gaebler (1992) claimed that to win publicsupport, government officials needed to demonstrate the results achieved. From this, onecould ascertain that local government should manage and measure its performanceusing PMS in order to better serve the citizens and in turn gain their support. As the formof government that is closest to the people, ILG has been recognised as the sphere ofgovernment that has the largest capacity to deliver real outcomes at a local level(LOGOTRI, 2003). This development, in turn, should increase the quality of life for itscitizens. In order to do this, however, local government must have some way ofmeasuring the success, failure, and progress achieved in the pursuit of the objectives.
Increasingly, performance measurement is considered to be a vital tool for localgovernment to not only measure its activities, but also to then provide feedback intothe management process to help improve future performance (LOGOTRI, 2003).Further, the development and use of performance measures is considered a key elementof NPM implementation (Lapsley, 2008; Boston, 2011).
Research on performance measurement in the Indonesian public sector is quitescarce. One study by Riandi (2003) found there was still an expectation gap betweenlocal government authorities and the community about the public service delivery.This gap occurred due to the lack of relevant performance indicators available todistinguish success from failure in public services delivery (Mahsun, 2005). McLeod(2005, p. 1) examined the reform process in Indonesia as a whole and providedsome explanations from the private sector for what he saw as “demonstrably poorperformance” in Indonesia.
Adoption of PMS as an important component of management reform in the publicsector has become more prevalent in the last two decades. Some scholars claimed thatthe arguments for this movement were mainly rational or technical in nature, and thatPMS was adopted as an effort towards achieving an efficient and effective organisation(Andrews et al., 2006; Meier et al., 2006). As a result of PMS implementation it wasenvisaged that better substantive performance would occur due to the expected benefitsof enhanced efficiency, accountability, and quality of public service delivery. Forexample, Andrews et al. (2006) argued that PMS be included in both theoretical andempirical models of public sector organisational performance. However, a different pointof view is offered by institutional theory, which argues that the main reason underlyingorganisational change is gaining legitimacy rather than improving substantiveperformance (Ashworth et al., 2009). Reasons for the shift in characteristics, therefore,were not only due to rational or technical reasons, but often political or legitimising ones(Ashworth et al., 2009; Scott, 1987).
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3. Theoretical frameworkIntroductionAs a theoretical framework, institutional theory is a very broad concept and has manystrands that have evolved since the development of the theory in the early twentiethcentury. The foundation of early institutionalism (old institutionalism) and itsapplication to organisations has been outlined by Selznick (1949, 1996). In contrast,modern institutionalism (new institutionalism) emerged in the 1970s, as has been shownin the work of Silverman (1971) followed by Meyer and Rowan (1977), Zucker (1977) andDiMaggio and Powell (1983) who extended Meyer and Rowan’s (1977) concept ofisomorphism to encompass the organisational field. Selznick (1996) compares the “old”with the “new” in an attempt to explain the differences – such as the definition ofinstitutionalisation – as well as promote the concept that institutional theory should beable to embrace all the classifications and definitions embedded in both the “old” and“new”. One major difference between the two is the view of the “institution”, withresearchers like DiMaggio and Powell (1991) espousing isomorphism and then thedoctrine of “power, subordination and responsibility” (Selznick, 1996, p. 272). Morerecently, academics have considered institutional theory in varying forms: Modell (2004,2005) and Tsamenyi et al. (2006) – utilise the new institutional sociology to explainorganisational change; Brignall and Modell (2000) – who consider that institutionaltheory could explore organisational change with the addition of the interests and powerfrom various stakeholders; Thornton and Ocasio (2008) – who contend that institutionallogics provide a bridge between some of the earlier institutional theories; Lounsbury(2008) – offers alternatives to isomorphism; Ashworth et al. (2009) – shows the benefitsof using isomorphism as an explanator of change; and Collin et al. (2009) – who suggestintegrating positive accounting theory with institutional theory.
It is obvious from this brief summary that institutional theory has many dimensions.In the field of organizational study, the concepts of institution and institutionalizationhave been defined in many different ways. One definition proposed by Scott (1987)was institutionalisation as a process of creating reality. This definition is relevanthere as this form of institutional theory is based on a shared social reality which, in turn,creates a human construction in social interaction. In other words, organisations(councils) operating in the same field (local government) react similarly and, over time,develop similar responses or adopt similar practices when facing certain situations.DiMaggio and Powell (1983, p. 147) explain: “Institutionalization is a rational response;one of the key outcomes of institutionalization is a homogeneous organizationalstructure.” Debate around nuances associated with variations on the “old” and then“new” institutional theory continue today (Falkman and Tagesson, 2008; Lounsbury,2008; Ashworth et al., 2009). Although many of these nuances would have fitted with theresearch objective here (for example, that proposed by Schneiberg and Soule (2005)which considered political and cultural aspects of the diffusion process), the moretraditional form of institutional isomorphism was used to inform the instrument and itssubsequent analysis. As a developing country, in many ways Indonesia is still in itsinfancy in regards to the development of PMS – particularly during the first wave ofreforms. Coercive and normative pressures played a role in the adoption process as willbe explained in the discussion section below.
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IsomorphismDiMaggio and Powell (1983) proposed that over time, in a well-established field,organisations tend to move towards homogenisation, even though they show considerablediversity at first. The term used that best describes the process of homogenisation isisomorphism. Although there are said to be different types of isomorphism (Meyer andRowan, 1977; DiMaggio and Powell, 1983), institutional isomorphism is used here. It isa useful concept in an environment where “politics and ceremony” (DiMaggio and Powell,1983, p. 150) are embedded in organizational life. Meyer and Rowan (1977, p. 348) arguethat isomorphism had three consequences for organisations:
(a) they incorporate elements which are legitimated externally, rather than in terms ofefficiency; (b) they employ external or ceremonial assessment criteria to define the valueof structural elements; and (c) dependence on externally fixed institutions reduces turbulenceand maintains stability.
DiMaggio and Powell (1983) identified three isomorphic forces – coercive, mimetic andnormative. Given this is not a longitudinal study, the first and latter isomorphicpressures are considered for this project. Coercive isomorphism stems from politicalinfluence and the pursuit of legitimacy. This pressure comes from both formal andinformal pressures from other organizations. Normative isomorphism, on the otherhand, is usually associated with professionalism and the way both formal and informalcollaboration can lead to more homogenisation of organisations.
Despite myriad views on other aspects of institutional theory and questionsregarding its applicability, institutional isomorphism is still being used successfullyworldwide (see for example, Tuttle and Dillard (2007) – USA; Kim et al. (2009) – Korea;Arnaboldi et al. (2010) – Italy).
Performance measurement and isomorphismOver the years management control systems with performance measurement playingan integral role, have been studied from functionalist, behavioural, interpretive andcritical perspectives. Recent studies, however, have been particularly influenced byinstitutional theories (Berry et al., 2009). Studies that adopted this theory assumed thatorganizations compete not only for resources and customers but also for politicalpower and institutional legitimacy. Institutional theory suggests that organizationspursue “legitimacy by conforming to isomorphic pressures in their environment”(Ashworth et al., 2009, p. 1). Therefore, from this perspective, the logics of change inPMS are institutionalized into organizations by means of three processes: coercive,mimetic, and normative (DiMaggio and Powell, 1983).
This study investigates the implementation of PMS in ILG and considers seniorfinance officers’ perceptions of performance measurement within an institutional theoryframework. The way performance measurement is used within government may dependon the power relationship between its constituents and itself (Pilcher and Dean, 2009).Demonstrating this, Pilcher (2011, p. 368) examined local government’s reporting undera performance measurement regime designed to ensure councils “performed orperished”. Brignall and Modell (2000, p. 282) also examined the implementation of PMSand claimed that to extend previous research in the area, it was necessary to “shiftthe attention to the power and pressures exerted by different groups of stakeholdersand how these affect the use of performance information in organisations.”
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Hence, in a decentralised government, such as Indonesia, the central authority normallyhas greater coercive power over local government than other constituents.
In Indonesia, the sources of isomorphic pressures potentially come from centralgovernment via enactment of laws and regulations that will affect local government.These regulations include Inpres No. 7/1999 that requires all government entities,including local government, to report on performance to central government. Thiscoercive pressure tends to occur due to most local governments being heavily dependenton central government for their financial resources or recognition via some awardsystem. Even though ILGs are required to submit performance reports to centralgovernment, this does not mean that they actually use performance information in theirday-to-day management practices (as found by various authors, including, for example,in a US study by de Lancer Julnes and Holzer (2001)). Therefore, an understanding offactors influencing the development and use of performance measures is important.The knowledge of these factors could be utilized to evaluate and improve futuregovernment policy. Although policy adoption has been said to rely on “factors fromrational and technocratic theory” (de Lancer Julnes and Holzer, 2001, p. 693), actualimplementation is more complex and is influenced by “political and culturalconsiderations” (de Lancer Julnes and Holzer, 2001, p. 693). Hence, thisstudy contributes to the literature and understanding by government policymakersby considering factors associated with development and use of performance measuresin Indonesia.
The third of DiMaggio and Powell’s (1983) isomorphic pressures, but the second tobe used here, is normative isomorphism. This element of pressure is normallydeveloped by professional and occupational groups (Rahaman et al., 2004). Given thelow level of human resources capacity in ILGs, there has been a trend in the last decadeto give more attention to the education of government employees and managers. As thedemand emerged, many universities in Indonesia have offered programmes (degree andnon-degree) that are specially designed to respond to government employees andmanagers’ needs. DiMaggio and Powell (1983) argued that the more educated theworkforce becomes, in terms of academic qualification and participation inprofessional and trade associations, the greater the extent to which the organizationbecomes similar to other organizations in the field.
4. Research model and hypotheses formulationThe objective of this research is to develop a conceptual model that identifies the factorsthat influence the development and use of performance indicators in ILG. The primaryresearch question is:
RQ1. What factors affect the development and use of performance indicators andaccountability practices in ILG?
The issues identified in previous studies were used to formulate the theoreticalframework described in Section 3 and secondary research questions that drive theresearch:
RQ2. Do metric difficulties, technical knowledge, management commitment, andlegislative requirements influence the development and use of performanceindicators in ILG?
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RQ3. Does institutional isomorphism exist in the development and use of PMS andaccountability practices in ILG?
The conceptual model outlined in this paper combines components of the accountabilitymodel of Wang (2002) with the model of performance measurement from Cavalluzzo andIttner (2004). It is modified and extended here to not only fit within the ILG context butalso to be analysed within an institutional theory framework. Cavalluzzo and Ittner’s(2004) study considered factors associated with performance measurement in the USGovernment. Questions related to the first four dependent variables (described andtabulated in Appendix 1) were adapted from their study with one major difference beingthe modification of five items (1, 2, 3, 5, and 6 under development of indicators inAppendix 2) to include a family of measures derived from the Indonesian LAKIPguidelines. In regards to the final dependent variable – external accountability – Wang’s(2002) model (in itself a permutation of items from other sources) was used as a templateand the eight items from the performance accountability construct were adjusted to suitthe ILG context.
In regards to the five independent variables, questions were again adapted fromCavalluzzo and Ittner (2004) for the first four variables whilst four items were takenfrom Wang (2002) to measure the level of organisational capacity (the final independentvariable). Again, differences existed with the first relating to “technical knowledge”which, although based on the “training” construct in Cavalluzzo and Ittner (2004),differs in the areas it addresses so that it fits with the ILG environment (and, again,LAKIP). Legislative requirements are also based on LAKIP. Combining components ofeach of these two studies not only allowed for a comprehensive examination of factorsaffecting the development and use of performance indicators, but also provided animportant aspect for ILG – particularly within NPM – being accountability. Hence,all three research questions detailed above could be addressed.
Figure 1 shows the conceptual model tested in this analysis and Appendix 1contains a copy of the constructs used in the model.
The hypothesised relationships between the independent and dependent variablesare discussed in the following sections along with the hypotheses proposed.
Dependent variablesDevelopment and use of performance indicators. Various studies regarding the use ofperformance measurement conducted in local government suggest that the practice ofcollecting performance indicators, at least at a rudimentary level, is fairly wellestablished in many countries, including the USA, the UK and Australia (Pilcher andDean, 2009). Despite this growing practice, previous studies found that the developmentand use of performance indicators in the public sector is problematical with very few localgovernments using performance indicators (Bellamy and Kluvers, 1995; Ammons, 1995).
As shown in Figure 1, the model includes five dependent variables:
(1) development of performance indicators;
(2) managerial use of indicators;
(3) higher use of indicators;
(4) internal accountability; and
(5) external accountability.
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In this study, development, accountability and use of performance indicators areassessed by asking respondents to answer a series of survey questions that refer to thedevelopment and adoption of different types of performance measures used by theorganisation. The first construct reflects the extent of performance indicatorsdeveloped by ILG organisations. Managerial use of indicators refers to the extent towhich performance indicators are used by mid-level managers to manage theorganisation. Higher use of indicators refers to measures that are used by top-levelmanagement to make funding decisions and manage high-level changes.Accountability in local government is measured by financial and non-financialperformance indicators. The internal accountability construct determines the extent ofthe accountability relationship between the supervisor and subordinate (for example,in ILG between the general manager and the council members), whereas the externalaccountability construct measures the extent of the relationship between ILGorganisations and their stakeholders (refer to Cheng (1994), for an example of themyriad stakeholders associated with local government).
Figure 1.Conceptual model
MetricDifficulties
TechnicalKnowledge
ManagementCommitment
LegislativeMandates
OrganisationalCapacity
Development ofIndicator
InternalAccountability
ExternalAccountability
Managerial Useof Indicator
Higher Useof Indicator
Notes: P < 0.001 and P < 0.01; P < 0.05; no association
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Independent variablesThere were five independent variables identified within the model (Figure 1):
(1) metric difficulties;
(2) technical knowledge;
(3) management commitment;
(4) legislative requirement; and
(5) organisational capacity.
Metric difficulties. The first independent variable refers to measurability of organizationaloutput or outcome. In other words, it considers the ability to “define and assess metricsthat capture desired actions and outcomes” (Cavalluzzo and Ittner, 2004, p. 247). In publicsector organizations the complexity of programmes is not always the same. Some outputsand effects are relatively easy to measure yet some are more difficult. For example, inIndonesia, Mahmudi (2003) found that local government managers had difficultiesin determining higher level indicators such as outcome, benefit and impact, therefore inpractice they placed more weight on input measures rather than outcome measures. Giventhe situation in Indonesia it is logical to expect that there will be a tendency in performancemeasurement users to give more weight to the easy-to-measure indicators:
H1a. Development of performance indicators is negatively associated with metricdifficulties.
H1b. Managerial use of performance indicators is negatively associated with metricdifficulties.
H1c. Higher use of performance indicators is negatively associated with metricdifficulties.
Technical knowledge. An organizational factor that is expected to influence thedevelopment and use of performance indicators is the extent to which training on relatedknowledge is provided to support the implementation (Shields, 1995; Cavalluzzo andIttner, 2004). According to Sukarno (2006), a lack of understanding of systems designedto support the implementation of performance indicators has impacted on theirdevelopment. Technical knowledge enables improvement in the ability of internalstakeholders to understand and use PMS, and should positively improve thedevelopment and use of performance indicators (de Lancer Julnes and Holzer, 2001;Laurensius and Halim, 2005). Different types of efforts, from technical training to formaldegree programmes, have been undertaken in Indonesia to increase the knowledge ofgovernment employees and officers. From this perspective, normative mechanisms assuggested by DiMaggio and Powell (1983) may also take place in practice:
H2a. Development of performance indicators is positively associated with relatedtechnical knowledge.
H2b. Managerial use of performance indicators is positively associated with relatedtechnical knowledge.
H2c. Higher use of performance indicators is positively associated with relatedtechnical knowledge.
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Management commitment. Implementation of PMS in government requires changesin the operation, personnel, structure, or even culture of the organization. It is important tobuild high levels of commitment amount senior management first, followed by supportfrom middle managers and staff (Fernandez and Rainey, 2006). de Lancer Julnesand Holzer (2001) found that internal stakeholder support was positively related to theadoption of PMS. As well, management also provides the political support needed toencourage and motivate individuals who resist the innovation. In addition to financialresources, time and personnel, the existence of internal commitment, especially bytop-level management within an organization, is required for the successfulimplementation of performance reporting in Indonesia (Sukarno, 2006):
H3a. Development of performance indicators is positively associated withmanagement commitment.
H3b. Managerial use of performance indicators is positively associated withmanagement commitment.
H3c. Higher use of performance indicators is positively associated withmanagement commitment.
H3d. Internal accountability is positively associated with management commitment.
H3e. External accountability is positively associated with management commitment.
Legislative mandates. Institutional theory suggests that legislative mandates(or regulation requirements) is an organizational factor that is relevant to the successof reform implementation in government organizations (Brignall and Modell, 2000).Furthermore, in an institutional environment such as ILG which primarily depends onan external organization (i.e. central government) for its financial support, externalbodies have the authority to impose organizational practices on subordinate units.Consequently, subordinate organizations will implement the required practices, but theactual results tend to be superficial (Scott, 1987). The implementation process of InpresNo. 7/1999 on accountability in Indonesia was highly centralistic. Cavalluzzo and Ittner(2004) found that implementation of externally mandated PMS was merely executed tomeet legal requirements. This resulted in the measures having little influence on internaloperations. In other words, it was just more “to conform than to perform” (Barreto andBaden-Fuller, 2006, p. 1559). From this perspective, coercive mechanisms as suggestedby DiMaggio and Powell (1983) may take place in practice:
H4a. Development of performance indicators is positively associated withlegislation requirements.
H4b. Managerial use of performance indicators is positively associated withlegislation requirements.
H4c. Higher use of performance indicators is positively associated with legislationrequirements.
H4d. Internal accountability is positively associated with legislation requirements.
H4e. External accountability is positively associated with legislationrequirements.
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Organizational capacity. The final factor employed considers the impact oforganizational capacity/resources on accountability practices. Prior research foundthat insufficient resources were often a cause of implementation failure (Ammons andRodrigues, 1986). The importance of capable staff in regard to the intensive use ofperformance measurement information has been studied by researchers such as Wangand Berman (2001). They found a positive relationship between staff competence andperformance measures (Wang and Berman, 2001).
Furthermore, van Dooren (2005) argued that lack of resources is an issue in performancemeasurement practice. Laurensius and Halim (2005) found that in Indonesia resourceshave a statistically significant effect on developing performance indicators. These findingsconfirmed those of de Lancer Julnes and Holzer (2001) who claimed that committedresources had a significant effect on the development of performance indicators:
H5d. Internal accountability is positively associated with organizational capacity.
H5e. External accountability is positively associated with organizational capacity.
5. Research methodTable I provides a summary of the proposed model variables and the number of itemsused to measure each variable. The structural equation model offered here is dividedinto two key components; the measurement model and the structural model. Themeasurement model, or outer model, focuses on the relationship between the unobservedlatent variables that cannot be directly measured and the measurable items known as themanifest variables (Hair et al., 2012; Chapman and Kihn, 2009). The structural model,also known as the inner model, focuses on the hypothesised relationships or pathsbetween the latent variables (Hair et al., 2012). All of the measureable items used in thisresearch are classified as reflective indicators.
SurveyIn September 2008, surveys were sent to senior finance officers who are responsible forperformance reporting in all local governments across Indonesia[2]. The constructs usedto develop the questionnaire were adapted from surveys used in Western countries(Cavalluzzo and Ittner, 2004; Wang, 2002), hence all the questions needed to be translatedfrom English into Bahasa Indonesia. There are several techniques available with thedirect translation method, and a relatively simple and straightforward but effective
Latent variable Short code Manifest variables No. of items
Development of indicator Dev Dev1 to Dev7 7Managerial use of indicator Muse MUse1 to Muse8 8Higher use of indicator HUse HUse1 to HUse3 3Internal accountability IAcc IAcc1 to IAcc4 4External accountability EAcc EAcc1 to EAcc8 8Metric difficulties Met Met1 to Met5 5Technical knowledge Kno Kno1 to Kno5 5Management commitment Com Com1 to Com3 3Legislative mandate Leg Leg1 to Leg2 2Organisational capacity Cap Cap1 to Cap4 4
Total 49Table I.Research model variables
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method was used here (Usunier, 1998). A qualified and experienced translator fromthe National Accreditation Authority for Translators and Interpreters was invited totranslate the questions and instructions used in the research instruments. To mitigatethe disadvantage of direct translation, the study conducted a pilot test to ensure thata satisfactory level of reliability was achieved (Usunier, 1998).
As of 2008, there were in total 457 local governments within 33 provinces with a totalpopulation of 230 million (Indonesian Bureau of Statistics, 2011). Of these, 211 werenewly established as a result of the districts and cities separation process over theprevious five years. Table II presents the distribution of responses from the survey. Dueto invalid data, two responses were ineligible for further analysis and consequently only98 usable responses (equivalent to a 21.4 per cent effective response rate) were analysed.
Among the respondents, 44 per cent were from Java with 56 per cent fromouter-Java. Most respondents (78 per cent) came from districts and only 22 per centcame from cities. When comparing the response rate of local government by type, thesample is fairly comparable with 21.5 per cent from districts and 23.2 per cent fromcities. With regard to location, there was only a 16.4 per cent response rate fromouter-Java, whilst that from Java was 38.3 per cent. The relatively low response rate canbe explained by two factors. First, and the most likely reason, was the lack ofexperience in performance reporting of the 211 newly established local governments.This was supported by the fact that almost all responses were from local governmentsin existence long before the reform era (old local governments). Second, anecdotally,very low responses are normally expected from local governments in outer-Java.To ensure no response bias, the 14 late responses were compared to the 84 earlierresponses using the Mann-Whitney test (Field, 2009). Analysis revealed that for allvariables employed the mean rank between earlier and later responses was notsignificantly different.
Demographic information of the respondents is summarized in Appendix 2.One point worth highlighting is that only 9 per cent of the respondents were female and89 per cent were male (2 per cent missing). These figures are representative of thepopulation of the study given the fact that the percentage of female senior financeofficers in Indonesian civil servants is only 9.5 per cent.
6. PLS analysis and resultsSmartPLS 2.0 (Ringle et al., 2005) and SPSS 18 were used to assess the quality of thesurvey data and analyse the research model proposed. SmartPLS is a second
Sent (457) Received (100)Frequency % Frequency % Response rate (21.9%) (%)
LocationIn-Java 115 25.2 44 44.0 38.3Outer-Java 342 74.8 56 56.0 16.4TypeDistricts 362 79.2 78 78.0 21.5Cities 95 20.8 22 22.0 23.2
Note: Due to invalid data, two responses were excluded and 98 were further analysedTable II.
Distribution of responses
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generation structural equation modelling technique that has been used in a number ofaccounting studies (see Hall (2008), for a list of studies). It is particularly suited to thisstudy because of the small sample size and complexity of the proposed model(Hair et al., 2012). Several authors, including Barclay et al. (1995), suggest the samplesize should be no lower than ten times the number of items within the most complexconstruct of the model tested. Based on this rule, the sample size for this study wouldneed to be a minimum 80 cases (n ¼ 8 items related to managerial use of indicator andexternal accountability by ten). Here there are 98 valid cases in this study satisfyingthe requirement for a sound PLS analysis. One limitation of this rule is that it does notconsider factors such as size and reliability. Such factors are discussed shortly. What itdoes do is provide an estimate of the minimum sample size requirements and thushas been used by many for robust PLS estimations (Hair et al., 2012).
Data examinationScanning of data on a line-by-line basis confirmed the absence of errors and the data setwas ready for further SmartPLS procedures. As PLS regression analysis does notrequire the data to be normally distributed (Chin et al., 2003), tests for normality were notnecessary. As well, goodness-of-fit measures were not appropriate here. Instead, similarto the process used in prior PLS research, fit was evaluated by the overall incidence ofsignificant relationships between constructs and the explained variance of thedependent variables (Chapman and Kihn, 2009; Chenhall, 2005).
Five exogenous (dependent) variables and five endogenous (independent) variableswere employed in the model. Research indicates that a minimum of two indicators(i.e. questions) are needed to measure a construct (Kline et al., 1998; Rahim et al., 2001).In this research, the number of indicators used to measure each of the model variablesranged from two to eight, with only one variable (legislative mandates) having theminimum of two indicators.
Convergent validityThe measurement model of PLS analysis consisted of two phases: convergent validityfollowed by discriminant validity. The first phase assessed the model’s convergentvalidity using two measures: individual item reliability and internal consistency(Santosa et al., 2005). Individual item reliability measures the convergence of eachindicator variable on its associated construct. Item reliability is assessed by examiningthe loading (i.e. correlations) of the indicator with their respective construct.Convergence, then, is established by comparing the loadings with a certain benchmark.All indicator loadings used in this research were above the minimum requirement (0.4)suggested by Igbaria et al. (1997) and Hair et al. (2006).
The second convergent validity measure considers the internal consistency ofconstructs. Composite reliability was used (Fornell and Larcker, 1981) as it is consideredsuperior to the traditional measure of consistency (Cronbach’s a) because it does notdepend on the number of indicators. Adequate reliability is gained when compositereliability value is greater than 0.5. Here, all the constructs exhibited adequate reliability.Fornell and Larcker (1981) also suggest that convergent validity can be determined byusing a more conservative test, which is by considering the average variance extracted(AVE). AVE should equal or exceed 0.5 to be judged adequate and again all constructspresented here meet this requirement (Table III).
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Discriminant validityAt construct level, discriminant validity is adequate when the variance sharedbetween a construct and any other construct in the model is less than the variancethat construct shared with its indicators (Fornell, 1982; Fornell and Larcker, 1981).Regarding indicator level validity, Barclay et al. (1995) suggest that no indicatorvariable should load more highly on another construct than it does on the construct itis supposed to measure. Within SmartPLS, a technique known as cross loading ofconstructs is used to test the discriminant validity at both indicator and constructlevel. Table IV shows the results of the correlation of the constructs for each of themodel variables.
Table IV presents the correlation matrix of the construct and the square root ofAVE (in italics). Previous literature recommends that these tests are best tabulated asin Table IV because the off-diagonal items (correlation of constructs) must be less thanor equal to the bolded diagonal items (square root of the AVE) in the correspondingrows and columns (Barclay et al., 1995; Gefen et al., 2000). Table IV shows thatdiagonal values are greater than the off-diagonal values in their corresponding rowsand columns, therefore there should be no issues with discriminant validity ofthe constructs.
Cap Com Dev EAcc HUse IAcc Kno Leg MUse Met
Cap 0.758Com 0.390 0.907Dev 0.238 0.581 0.758EAcc 0.491 0.614 0.483 0.852HUse 0.224 0.490 0.501 0.424 0.881IAcc 0.275 0.620 0.442 0.642 0.644 0.790Kno 0.339 0.516 0.513 0.528 0.361 0.466 0.747Leg 0.189 0.505 0.510 0.491 0.361 0.507 0.515 0.928MUse 0.179 0.732 0.652 0.545 0.608 0.552 0.556 0.546 0.781Met 0.073 20.231 20.280 20.069 20.109 20.114 20.172 20.043 20.252 0.846
Note: Italicised diagonal are the square root of AVE
Table IV.Correlation of constructs
and the square rootof AVE
Construct Composite reliability Cronbach’s a a AVE
Development of indicator 0.904 0.876 0.574Managerial use of indicator 0.926 0.908 0.609Higher use of indicator 0.912 0.858 0.777Internal accountability 0.863 0.791 0.625External accountability 0.955 0.946 0.726Metric difficulties 0.926 0.901 0.716Technical knowledge 0.860 0.793 0.558Management commitment 0.933 0.892 0.823Legislative mandate 0.925 0.838 0.861Organizational capacity 0.904 0.876 0.574
Note: aPresented only for comparative purposes
Table III.Internal consistency
and AVE
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Structural model assessmentThe structural model focuses on the hypothesized relationships or paths between thelatent variables (Hair et al., 2006). A structural model can be used to draw conclusionsabout the significance of the relationship between constructs and to comment on thepredictive power of the model proposed.
Given the fact that SmartPLS does not assume a normal distribution of data, it isinappropriate to use traditional tests to ascertain the statistical significance betweenconstructs (Chin and Newsted, 1999). Instead, scholars of PLS have developed twononparametric approaches to test the relationship between variables; either jackknifeor bootstrap techniques (Gefen et al., 2000; Santosa et al., 2005). In this study bootstrapwas used as it is considered to be a more sophisticated approach than jackknife(Chin, 1998). It provides two measures of the structural model: a t-value (similar to thet-test) and R 2 (interpreted similarly to the traditional multiple regressions analysis).The predictive power of the research model can be assessed by using R 2 stemmedfrom the output of the bootstrap. Although prior research has confirmed the robustnessof using PLS for non-normal data, it has still been raised by some that highly skeweddata can increase bootstrap standard errors. However, findings by Hair et al. (2012),determined that reporting the extent to which data are non-normal is not often done byresearchers and those studies that do show that there is very little evidence ofsignificant differences. Table V shows the R 2 values for each of the dependentvariables in the model.
As indicated, R 2 values range from 0.265 to 0.607. The strongest R 2 value is that ofmanagerial use of indicator (0.607) which indicates that 60.7 per cent of use of indicatorsfor managerial level purposes can be explained by the constructs used in this model.The second strongest is for external accountability (0.497), while the lowest is that ofhigher use of indicator (0.265). All R 2 values meet the 0.10 minimum limit suggested by,for example, Santosa et al. (2005). The path coefficient results are shown in Table VI.The results range from the weakest of only 0.002 (for Met ! HUse) to the strongest of0.529 (for Com ! MUse).
Hypothesis testingTo test the hypotheses, it was necessary to interpret the construct equations with standarderrors and test statistics. The construct equations measure the extent to which one factorrelates to another, that is, the structural path coefficient and t-values betweenhypothesized constructs, reflecting direct relationships (Tabachnick and Fidell, 1996).These path coefficients and associated t-values identify and demonstrate the direction and
Construct R 2a
Development of indicator (Dev) 0.455Managerial use of indicator (MUse) 0.607Higher use of indicator (HUse) 0.265Internal accountability (IAcc) 0.437External accountability (EAcc) 0.497
Notes: a0.67 – substantial, 0.33 – moderate and 0.19 – weakSource: Henseler et al. (2009)
Table V.R 2 values
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strength of each relationship and, as indicated, are obtained by using the bootstrappingtechnique in SmartPLS software. “The t-values (robust scores) need to be significant tosupport the hypothesized paths and should be above 1.96 or 2.56 for alpha protection levelof 0.05 and 0.01, respectively” (Gefen et al., 2000, p. 35). Using this criterion, the results forthe structural relationships are reported in Table VI followed by an examination ofimplications for the hypotheses. The discussion of the results appears in Section 7 withFigure 1 (reviewed in Section 4) providing a graphical representation of the results.
Development of indicators (H1a-H4a)The results show a strong positive association between the development of indicators inILG and performance reporting legislation (H4a, p , 0.01). In other words, as newregulations related to performance reporting emerged, ILG responded promptly byproviding more indicators as required by those regulations. Further, the development ofperformance indicators in ILG increased as officers and staff gained more relatedtechnical knowledge offering support forH2a ( p , 0.05). The results also show supportfor H1a ( p , 0.05) and H3a ( p , 0.05). This indicates that metric difficulties arenegatively related to the development of performance indicators and that managementcommitment from ILG managers is positively related to the development of indicators.
Managerial use of indicators (H1b-H4b)The results reveal that the proposed relationship between management commitmentand managerial use of performance indicators (H3b) is highly significant ( p , 0.001)
Hypothesis Relationship Sign. Coeff. t-value
A. Development of indicatorH1a Met ! Dev – 20.162 1.956 *
H2a Kno ! Dev þ 0.195 2.224 *
H3a Com ! Dev þ 0.322 2.534 *
H4a Leg ! Dev þ 0.240 2.735 * *
B. Managerial use of indicatorH1b Met ! Muse – 20.092 1.500H2b Kno ! Muse þ 0.171 2.077 *
H3b Com ! Muse þ 0.529 7.243 * * *
H4b Leg ! Muse þ 0.187 2.346 *
C. Higher use of indicatorH1c Met ! HUse – 0.002 0.020H2c Kno ! HUse þ 0.108 0.854H3c Com ! HUse þ 0.377 3.498 * * *
H4c Leg ! HUse þ 0.115 0.987D. Internal accountabilityH3d Com ! IAcc þ 0.472 3.621 * * *
H4d Leg ! IAcc þ 0.261 2.298 *
H5d Cap ! IAcc þ 0.042 0.346E. External accountabilityH3e Com ! EAcc þ 0.374 3.449 * * *
H4e Leg ! EAcc þ 0.245 2.618 * *
H5e Cap ! EAcc þ 0.299 2.398 *
Notes: Significant at: *p , 0.05, * *p , 0.01 and * * *p , 0.001
Table VI.Summary of hypothesis
testing results
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and therefore supported. This result clearly indicates that the use of performanceindicators in ILG at managerial level is highly influenced by the commitment of ILG’stop-level management. The results also show the proposed relationships betweenlegislative requirements, technical knowledge and managerial use of performanceindicators (H4b and H2b) are both moderately significant ( p , 0.05) and hencesupported. This implies that the extent of use of performance indicators by mid-levelmanagement is affected by the level of their technical knowledge and legislativerequirements. The greater their level of knowledge, the more extensive the use ofperformance indicators. The results determine that there is no support for H1b,indicating that using performance indicators at the managerial level is not associatedwith the problems that exist in the process of developing performance indicators.In other words, and supporting prior literature (Mahmudi, 2003), once indicatorsbecome available, ILG’s managers just use them without a need to consider theproblems that existed when they were developed.
Higher use of indicators (H1c-H4c)The results reveal a strong positive association between the use of indicators at a higherlevel and the commitment of ILG management (H3c, p , 0.001). It is not surprising thatthe results provide no support for H1c. This suggests that higher level ILG managerssimply use the indicators that are provided to them. As for Cavalluzzo and Ittner’s (2004)findings, this is logical, given that in government (or in this case ILG), the responsibility ofdeveloping performance indicators is usually that of senior finance officers (or equivalent).Further, results offered no support for H2c, indicating that technical knowledge is not adeterminant in the use of performance indicators by higher level ILG managers.Finally, the results provided no support for H4c implying that, unlike at managerial level,the use of indicators in ILG at the higher level is unaffected by regulatorymandates received by ILG. It seems that regulations related to performance reporting(mainly imposed by central government) had no impact on level of use of indicators at ahigher level. This was inconsistent with the finding inH4b. ILG managers at a higher levelrespond differently to the regulatory mandates than those at managerial level.
Internal accountability (H3d-H5d )The results provide strong support for H3d ( p , 0.001) and moderate support for H4d( p , 0.05). This implies that the extent of internal accountability is influenced by boththe level of commitment by ILG officers and the amount of legislative mandatesimposed by central government. The results offer no support for H5d suggesting thatorganizational capacity (i.e. management information systems and staff capability)had no association with the extent of internal accountability practiced in ILGs.
External accountability (H3e-H5e)First, similar to the results for H3d, strong support for H3e ( p , 0.001) indicated thatthere was a positive association between external accountability and managementcommitment. This implies that the extent of external accountability provided by ILGsto their stakeholders was affected by management’s commitment to implementingPMS. The results also provide support for H4e ( p , 0.01) indicating that legislationmandates had an impact on the level of external accountability of ILG. It also suggeststhat the mandatory nature of performance reporting regulations did ensure
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improvement of external accountability of ILG. Finally, and contrary to the finding inH5d, the results provide moderate support for H5e ( p , 0.05). In other words,organizational capacity had an impact on the level of external accountability of the ILG.The higher the capacity of ILGs, the higher the level of external accountability.
7. DiscussionPerformance measurementPLS analysis, as shown in the previous section, provided significant results with supportfor many of the hypotheses. As expected, metric difficulties had a negative associationwith development of performance indicators, while the other three factors – technicalknowledge, management commitment, and legislative mandates – had a positivesignificant association. These supported findings in Cavalluzzo and Ittner (2004). Forexample, in their study, metric difficulties caused significant problems with the extent ofperformance measurement development whilst their equivalent to managementcommitment, legislative mandates and technical knowledge had a positive associationwith development. Findings here also revealed that the variable legislative mandateshad a strong association with development of performance indicators. This indicates thepotential existence of coercive isomorphism in ILG as management tend to be moreconcerned about legislative requirements than other more technical (metric difficultiesand technical knowledge) and normative (management commitment) factors. Bovairdand Downe (2006) found that organisations within the field of UK local government werehomogenised in their adaptation of externally mandated institutional pressures. Here,there is an indication that organisations in the field of ILGs developed performanceindicators more to fulfil regulatory requirements than to make their organizationmore effective and efficient. This is also consistent with other prior research on coerciveisomorphism such as that by Arnaboldi et al. (2010) who found that the decision bygovernment to adopt performance appraisal systems was forced on them by legislation,raising the presence of coercive isomorphism. As well, it supports our premise abovethat one of the main reasons for implementing PMS is to gain legitimacy rather thanimprove performance (Meier et al., 2006; Ashworth et al., 2009).
Contrary to expectation, H1b and H1c that metric difficulties have a negativeassociation with the use of performance indicators (both at managerial and higher level)was not supported by the results. This finding indicates that issues related tomeasurability did not affect the use of performance indicators by ILG managers one wayor the other. Mid- and top-level managers were impervious to how indicators weredeveloped and they only used indicators for formal reporting (legislative requirements)or political/ceremonial speeches – both reasons indicate strong support for the presenceof coercive isomorphism (and also supporting prior literature relating to isomorphismand political concerns, such as de Lancer Julnes and Holzer (2001). Findings also implythat metric difficulties are more troublesome when developing indicators than whenactually using them. Performance measurement was measured in two stages –development first and use second. Given this sequence, it is not surprising that theproblem with measurability did not affect the use of indicators as at this stage theindicators had already been developed.
Whilst support was found for H2b, that the use of indicators at managerial level waspositively associated with technical knowledge, it was not the case for the use at higherlevel (H2c). The implication here is that issues related to technical knowledge are more
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relevant at managerial levels than for higher levels. This may indicate that at manageriallevel ILG officers are more concerned with technical indicators while higher level officersnormally use more macro (high level) indicators which are less technical, thus easier tocomprehend. Furthermore, technical training on performance measurement for ILG isusually aimed at managerial and operational levels, not higher level managers. This,in turn, provides support for normative isomorphism. Widespread training by auditfirms and universities, and the sharing of this knowledge, assist ILGs to maintainlegitimacy. This dissemination of information is most common at managerial level.
In line with expectations, the positive association between management commitmentand use of indicators both at managerial and higher levels (H3b and H3c) was highlysupported. This finding is not surprising given organizational commitment is extremelyvaluable. What was surprising, given Cavalluzzo and Ittner’s (2004) findings, was thatuse at managerial level was supported as their study only determined support for higherlevel use. Other literature, such as Fernandez and Rainy (2006), contends that successfulchange relies on participation by employees along with direction and commitment frommanagement. de Lancer Julnes and Holzer (2001) also found that commitment has apositive impact on the use of indicators. In a country (Indonesia) that is relativelynew to a decentralised form of government, commitment to use at both levels is anencouraging finding.
With regard to legislative mandates, the results were mixed. Support was found forH4b that managerial use of indicators was positively associated with legislativemandates, but that was not the case for higher use (H4c). As in technical knowledge, theconcern about regulation is also more relevant at managerial level than at the higherlevel. Again this differed from Cavalluzzo and Ittner (2004), where there was noassociation found for use at either level. Since the emergence of regulation on LAKIP in1999, more technical indicators were expected to be developed and then reported in anILG performance report. This requirement placed more pressure on managerial levelofficers who deal with the use of technical indicators than higher level officers who areexpected to use higher level indicators that, again, are less technical. With pressure fromcentral government to comply with legislative requirements linked to funding, coercivepressure is felt by those at managerial level.
AccountabilityThe research found that the existence of leadership was critical to the success ofdeveloping and using performance indicators in ILG. It is generally expected that thesuccess of performance measurement implementation, in turn, will increase anorganization’s internal and external accountability. Both internal and externalaccountability were associated with management commitment. Wang (2002) foundassociations between internal accountability and leadership or management commitment,however, not between external accountability and management commitment. Supporthere was also found for the variable legislative mandate. This indicates that one importantfactor that makes ILG discharge accountability is legislative requirement. The pressuresfrom central government were still strong despite decentralization being in place fora decade. This indicates the potential existence of coercive isomorphism.
With regard to organizational capacity (i.e. MIS, human resources capability), resultswere mixed – which was unexpected. Organisational capacity is crucial to ensuresuccess of an organisation, including achieving accountability goals. Strong support for
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the relationship between organisational capacity and accountability was consequentlyexpected – however, this was not found to be the case here. Organisational capacity hada strong relationship with external accountability but not with internal accountability.One explanation for this inconsistency is that it does not require many resources toincrease internal accountability, but rather it needs commitment from both the leaderand the subordinates. Therefore, any ILG, regardless of its organisational capacity,has the potential to improve internal accountability within its organisation. Conversely,it is not an easy task for many ILGs to fulfil external accountability. Dischargingaccountability to external stakeholders is risky and more complex than that to internalmanagement. Accountability can be perceived by stakeholders to exist when humanresources receive further training and education. Interacting on a professional basis withothers at this training coincides with normative isomorphism.
8. ConclusionFrom the study we can answer RQ1 that in an ILG environment there is evidence thatfour organizational factors (metric difficulties, technical knowledge, managementcommitment, and legislative requirements) have an impact on the development ofperformance indicators. Of these four factors, legislative requirement has the strongesteffect. This implies that the main reason for developing indicators is simply to complywith central government regulation. In other words, the motivation is more aboutconformance than performance, and coercive pressure is strongest from centralgovernment. This, and the further suggestions of isomorphic pressures discussedbelow, helps answer RQ2 implying that ILGs are not using the indicators effectively.
Second, metric difficulties is the only factor that has no effect on using performanceindicators at managerial level. Technical knowledge through formal (e.g. training) orinformal (e.g. professional group meetings) means had an impact on managerial levelofficers’ use of performance indicators. Normative isomorphism played a positive role inthe understanding and sharing of knowledge at this level. On the other hand, managementcommitment had an effect on the use of performance indicators at both levels, managerialand higher level ILG managers. This was contrary to much of the prior literature and animportant contribution of this research study. Third, all three independent variablestested – management commitment, legislative requirement, and organizationalcapacity – are evidenced to have influence on external accountability. Similar to theresults achieved analysing the use of performance indicators, in regard to both internaland external accountability the strongest factor is management commitment.
Institutions need to confirm their legitimacy to their various stakeholders and hencetop-level managers in ILG need to give their full commitment to using PMS.If stakeholders, whether they be the citizens or central government, can see ILGs arecommitted to using performance indicators, funding and recognition via awards can beforthcoming. As indicated earlier, Meyer and Rowan (1977) claimed that isomorphismhad three consequences for organisations; those three consequences have been found tobe relevant here. First, PMS was implemented so that the ILG could be legitimatedexternally; second, the fact that central government based their funding and awardcriteria on the submission of the performance report influenced the ILGs decision toimplement; and finally, implementation meant being part of an organisational field thatwas dependent on central government and hence this reduced “turbulence andmaintained stability” (Meyer and Rowan, 1977, p. 348).
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Academically, the model – as adapted and modified for this study – can now be usedin other developing countries to analyse similar factors. As well, with its unique use ofSmartPLS in the given context, this paper lays the foundation for further exploration ofother theories. In saying that, in this particular environment, institutional isomorphismprovided an excellent lens through which to explore and explain the possible motivationsbehind the development and use of PMS. Although there have been many recentsuggestions (Schneiberg and Soule, 2005; Falkman and Tagesson, 2008; Lounsbury,2008) of other ways institutional theory can be relevant, this should not detract from thework of the early authors such as Meyer and Rowan (1977) or DiMaggio and Powell (1983,1991) and the strength of institutional isomorphism as shown here.
Practically, a major contribution of this research is that it provides an understandingof factors influencing the development and use of performance measures in Indonesiaand, in particular, in local government. Cavalluzzo and Ittner (2004) found thatimplementation of externally mandated PMS in US Government organisations was usedmerely to fulfil regulatory requirements, and tended to be symbolic in nature, withoutsubstantive impact on internal operations. The Indonesian Government at every tier hasembraced PMS and reported performance since the reform process began. Findings herewill assist local and central government, accountants, auditors, professional bodies anduniversities – to name a few – have more of an understanding of the factors influencingthe development and use of performance measures in Indonesia. Further, they will assistwith future research in other developing countries. The knowledge of these factorscould, in turn, be utilised to evaluate and improve or even formulate future governmentpolicy. Local government is the government closest to the citizens and provision ofquality services as measured by effective performance indicators would be an idealoutcome. Finally, to enhance external accountability more interaction and/or trainingcould assist stakeholders (putting normative isomorphism to good use) to have more ofan understanding of PMS, and accountability may not then be such an onerousrequirement. Future research will consider how performance indicators are used by thevarious ILG stakeholders. Another area of future research is to consider why in ILGmanagement commitment had an effect on the use of performance indicators by bothlevels of managers. Is ILG doing something other countries/organisations could adapt?Finally, future research will explore the development and use of PMS in other developingnations and whether alternative theories can provide as rich results as offered here.
Notes
1. A list of acronyms is available in Appendix 3.
2. If you would like a copy of the survey please contact the author.
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Further reading
de Lancer Julnes, P. (2006), “Performance measurement: an effective tool for governmentaccountability? The debate goes on”, Evaluation, Vol. 12, p. 219.
Drucker, P.F. (1999), Management: Tasks, Responsibilities, Practices, Butterworth-Heinemann,Oxford.
Indonesian Government (1999), Laporan Akuntabilitas Kinerja Institusi Pemerintah/GovernmentInstitution Accountability of Performance Report (LAKIP ) – Presidential Instruction InpresNo. 7/1999, Indonesian Government, Yogyakarta, Indonesia.
Wang, J. (2007), “An alternative approach to conceptualizing interviews in HRD research”,Human Resource Development Quarterly, Vol. 18 No. 2, p. 179.
(The Appendices follow overleaf.)
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Appendix 1
No.
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stru
ctIt
ems
1D
evel
opm
ent
ofin
dic
ator
sD
ev1:
inp
ut
(i.e
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tyof
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ome
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cy(i
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it)
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ce)
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eria
lu
seof
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ing
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yan
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orit
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urc
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ng
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pro
ach
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ork
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ord
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ing
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gra
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fort
sw
ith
oth
erin
tern
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atio
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se5:
refi
nin
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per
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ance
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sure
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ent
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ise
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igh
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ors
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sfr
omm
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itie
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dg
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nd
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isio
ns
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my
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sure
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ang
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ym
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ove
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ased
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rman
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res
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tern
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als
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yle
vel
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hel
dac
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ble
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lts
ofth
eir
acti
vit
ies
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plo
yee
sin
my
LG
rece
ive
pos
itiv
ere
cog
nit
ion
for
hel
pin
gth
eL
Gac
com
pli
shst
rate
gic
goa
lsIA
cc3:
the
ind
ivid
ual
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por
tto
per
iod
ical
lyre
vie
ws
my
acti
vit
y’s
resu
lts
wit
hm
eIA
cc4:
lack
ofin
cen
tiv
es(e
.g.
rew
ard
,p
osit
ive
reco
gn
itio
n)
has
hin
der
edu
sin
gp
erfo
rman
cein
form
atio
n5
Ex
tern
alac
cou
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bil
ity
EA
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org
anis
atio
n-w
ide
pol
icy
pri
orit
ies/
goa
lsE
Acc
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rog
ram
goa
lsan
dob
ject
ives
EA
cc3:
pro
gra
mfu
nct
ion
san
dac
tiv
itie
sE
Acc
4:p
rog
ram
outp
ut
mea
sure
sE
Acc
5:p
rog
ram
outc
ome
mea
sure
sE
Acc
6:p
rog
ram
nar
rati
ve
per
form
ance
info
rmat
ion
EA
cc7:
tren
ds
ofp
erfo
rman
cem
easu
res
EA
cc8:
com
par
ison
sof
per
form
ance
mea
sure
s
(continued
)
Table AI.Constructs usedin the model
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No.
Con
stru
ctIt
ems
6M
etri
cd
iffi
cult
ies
Met
1:d
iffi
cult
yd
eter
min
ing
mea
nin
gfu
lm
easu
res
Met
2:re
sult
sof
our
pro
gra
m(s
)/op
erat
ion
(s)/
pro
ject
(s)
occu
rrin
gto
ofa
rin
the
futu
reto
be
mea
sure
dM
et3:
dif
ficu
lty
dis
tin
gu
ish
ing
bet
wee
nth
ere
sult
sp
rod
uce
db
yth
ep
rog
ram
and
resu
lts
cau
sed
by
oth
erfa
ctor
sM
et4:
dif
ficu
lty
det
erm
inin
gh
owto
use
per
form
ance
info
rmat
ion
toim
pro
ve
the
pro
gra
mM
et5:
dif
ficu
lty
det
erm
inin
gh
owto
use
per
form
ance
info
rmat
ion
tose
tn
ewor
rev
ise
exis
tin
gp
erfo
rman
ceg
oals
7T
ech
nic
alk
now
led
ge
Kn
o1:
Ire
ceiv
etr
ain
ing
ond
evel
opm
ent
and
use
ofp
erfo
rman
cem
easu
res
Kn
o2:
my
staf
fre
ceiv
etr
ain
ing
ond
evel
opm
ent
and
use
ofp
erfo
rman
cem
easu
res
Kn
o3:
Ire
ceiv
ep
ub
lish
edin
form
atio
non
how
tod
evel
opp
erfo
rman
cem
easu
res
Kn
o4:
my
staf
fre
ceiv
ep
ub
lish
edin
form
atio
non
how
tod
evel
opp
erfo
rman
cem
easu
res
Kn
o5:
my
LG
inv
olv
eex
tern
alex
per
tsor
con
sult
ants
ind
evel
opin
gp
erfo
rman
cem
easu
res
8M
anag
emen
tco
mm
itm
ent
Com
1:m
yin
stit
uti
on’s
top
lead
ersh
ipd
emon
stra
tea
stro
ng
com
mit
men
tto
ach
iev
ing
resu
lts
Com
2:th
ela
ckof
ong
oin
gto
pex
ecu
tiv
eco
mm
itm
ent
orsu
pp
ort
for
usi
ng
per
form
ance
info
rmat
ion
tom
ake
pro
gra
m/f
un
din
gd
ecis
ion
sh
ind
ered
mea
suri
ng
per
form
ance
oru
sin
gp
erfo
rman
cein
form
atio
n?
Com
3:th
ela
ckof
ong
oin
gco
ng
ress
ion
alco
mm
itm
ent
orsu
pp
ort
for
usi
ng
per
form
ance
info
rmat
ion
tom
ake
pro
gra
m/f
un
din
gd
ecis
ion
sh
ind
ered
mea
suri
ng
per
form
ance
oru
sin
gp
erfo
rman
cein
form
atio
n?
9L
egis
lati
ve
req
uir
emen
tsL
eg1:
Ih
ave
bee
nin
vol
ved
inm
ylo
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Table AI.
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Appendix 2
Appendix 3. List of acronyms
AVE – average variance extracted
ILG – Indonesian local government
Inpres – Instruksi Presiden/Presidential Instruction
LAKIP – Laporan Akuntabilitas Kinerja Institusi Pemerintah/Government InstitutionAccountability of Performance Report
LOGOTRI – Local Government Training and Research Institute
NGO – non-government organisation
NPM – new public management
OLS – ordinary least squares
PLS – partial least squares
PMS – perforance measurement systems
SEM – structural equation modelling
Research model variables – short codes
Dev – development of indicator
Muse – managerial use of indicator
Characteristics Frequency Percentage
Gender Female 9 9.2Male 87 98.8
Missing 2 2.0Age group ,30 1 1.0
30-40 12 12.241-50 36 36.7.50 44 44.9
Missing 5 5.1Education level Undergraduate 33 33.7
Post-graduate 63 64.3Missing 2 2.0
Field background Accounting 2 2.0Others 87 88.8
Missing 9 9.2Work experience ,2 1 1.0
2-5 3 3.16-10 6 6.111-15 32 32.7.15 43 43.9
Missing 13 13.3Type District 76 77.6
City 22 22.4Location In-Java 43 43.9
Outer-Java 55 56.1
Table AII.Demographic informationof respondents (n ¼ 98)
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Huse – higher use of indicator
IAcc – internal accountability
EAcc – external accountability
Met – metric difficulties
Kno – technical knowledge
Com – management commitment
Leg – legislative mandates
Cap – organisational capacity
About the authorsDr Rusdi Akbar is a Lecturer in the Faculty of Economics at the Universitas Gadjah Madain Indonesia.
Dr Robyn Pilcher is an Associate Professor in the School of Accounting at Curtin University,Australia. Robyn Pilcher is the corresponding author and can be contacted at: [email protected]
Dr Brian Perrin is a Senior Lecturer in the School of Accounting at Curtin University,Australia.
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This article has been cited by:
1. Rusdi Akbar, Robyn Ann Pilcher, Brian Perrin. 2015. Implementing performance measurement systems.Qualitative Research in Accounting & Management 12:1, 3-33. [Abstract] [Full Text] [PDF]
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