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The authors examine how the major board reforms recently implemented by countries around the world affect firms' choice of debt.

Using a quasi-experimental setting of major board reforms around the world that aim to improve board-related governance practices in various areas, this study investigates the impact of effective board monitoring on corporate debt choice. The authors employ difference-in-differences-type quasi-natural experiment method and path analysis for hypotheses testing.

The authors find that the implementation of board reforms is positively associated with firms' preference for public debt financing over bank debt. However, this effect tends to weaken after the fourth year following the implementation of board reforms. In additional analyses, the authors find that “rule-based” reforms have a more pronounced effect on firms' choice of debt than do “comply-or-explain” reforms. Both (1) strengthened firm-level internal governance practices that address concerns about the agency cost of debt and (2) reduced information asymmetries play important roles in facilitating firms' debt choice, but the evidence suggests that the former is the economic mechanism through which country-level reforms affect corporate debt choice.

The study extends the literature examining the heterogeneity of corporate debt choices in a global setting and the literature on the consequences of corporate governance reforms.

The findings demonstrate the effectiveness of the corporate board reforms implemented in countries around the world, addressing concerns from critics about their potential harm or ineffectiveness.

The results indicate that country-level board reforms reduce the extent to which shareholder–creditor conflicts harm shareholders.

The purpose of this paper is twofold. First, the authors investigate a firm’s decision to provide a CSR report, and if so, whether to have the report assured and to seek higher quality assurance as reflected through the choices of the scope of the assurance and type of assurer, Big 4 accounting firm vs specialist consultant. Second, the authors investigate the impact of voluntary assurance of CSR reports, assurance scope and type of assurer on the likelihood of inclusion in the DJSI and on market valuation.

The study’s sample consists of 17,050 firm-year observations from 40 countries with CSR reports available from Corporate Register and ESG metrics available from ASSET4 over the period 2009–2015. The study first empirically examines the associations between CSR commitment and each of CSR report provision, CSR report assurance, assurance scope and type of assurer. It then examines that association between both inclusion in the DJSI and market valuation with each of CSR report assurance, assurance scope and type of assurer, using inclusion in the DJSI as an objective measure of a firm’s reputation for sustainability given its recognition as a leading indicator for corporate sustainability and market valuation as a reflection of the broader set of capital market participants.

The authors establish two key findings consistent with the predictions of signaling theory. First, we show that high CSR commitment firms are more likely to: provide standalone CSR reports; obtain assurance; obtain assurance from a Big 4 accounting firm; and, adopt higher assurance scope. Second, the authors find that both CSR report assurance and assurance scope increase the likelihood of inclusion in the DJSI, but that the type of assurance provider does not. Alternatively, the authors find that capital market participants appear to value the provision of a CSR report only when it is assured by a Big 4 accounting firm.

The results in the existing literature exploring the capital market benefits to CSR Assurance have been mixed. Firms that voluntarily obtain CSR Assurance incur a cost in doing so and must perceive a net benefit from obtaining such assurance. Despite the limited guidance currently provided by existing CSR standards, we establish the existence of benefits to obtaining CSR Assurance in terms of enhanced likelihood of DJSI inclusion and, more generally, enhanced market valuation. The discussions with DJSI analysts indicate that CSR assurance does enhance the perceived reliability of CSR data, thus improving user confidence.

The contemporary business environment has raised the strategic importance of the maintenance function in organizations which have significant investment in physical assets. Four strategic dimensions of maintenance management are identified, namely service‐delivery options, organization and work structuring, maintenance methodology and support systems. The alternatives available are reviewed: the guidelines for selection of these alternatives, the key decision areas in each of the four dimensions, as well as the critical success factors for the transformation process are discussed. The two factors that permeate in these strategic dimensions are human factors and information flow; the latter can be made more efficient by embracing the e‐maintenance model.

The purpose of this paper is to present a study on the relationship between the client and the contractor in a multi‐contractor business network.

A model built on transaction cost economics and relational exchange theory is proposed to determine the preferred governance mechanism as a function of fit with the technical environment of facilities management. Hypotheses in the model are tested by means of data collected from a survey of facilities managers.

It is found that decision making uncertainty has a negative effect on relational norm. On the other hand, a positive relationship exists between asset specificity and relational norm, and this relationship is moderated by risk of malfunction.

As trust and relational norm may be affected by the local culture, validation of the study may be necessary in other cultural settings.

By means of the empirical model, the gap between the current relational norm and the desired relational norm can be determined. With this knowledge, the facilities manager of the client can then plan change initiatives to narrow the gap.

The developed regression equation facilitates objective determination of the preferred relational norm between the client and the contractor in the context of maintenance out‐tasking.

This paper aims to discuss and bring to the attention of researchers and practitioners the data management issues relating to condition‐based maintenance (CBM) optimization.

The common data quality problems encountered in CBM decision analyses are investigated with a view to suggesting methods to resolve these problems. In particular, the approaches for handling missing data in the decision analysis are reviewed.

This paper proposes a data structure for managing the asset‐related maintenance data that support CBM decision analysis. It also presents a procedure for data‐driven CBM optimization comprising the steps of data preparation, model construction and validation, decision‐making, and sensitivity analysis.

Analysis of condition monitoring data using the proportional hazards modeling (PHM) approach has been proved to be successful in optimizing CBM decisions relating to motor transmission equipment, power transformers and manufacturing processes. However, on many occasions, asset managers still make sub‐optimal decisions because of data quality problems. Thus, mathematical models by themselves do not guarantee that correct decisions will be made if the raw data do not have the required quality. This paper examines the significant issues of data management in CBM decision analysis. In particular, the requirements of data captured from two common condition monitoring techniques – namely vibration monitoring and oil analysis – are discussed.

This paper offers advice to asset managers on ways to avoid capturing poor data and the procedure for manipulating imperfect data, so that they can assess equipment conditions and predict failures more accurately. This way, the useful life of physical assets can be extended and the related maintenance costs minimized. It also proposes a research agenda on CBM optimization and associated data management issues.

The reliability and maintainability of tunnel infrastructure and systems is an important factor in assuring normal operation of a tunnel. Evaluating availability of a large‐scale tunnel that includes civil, electrical, mechanical and electronic systems is a difficult task. The purpose of this paper is to present a methodology for performing such assessments, featuring the use of the Markov model.

The methodology involves application of failure mode, effect and criticality analysis (FMECA), state space diagram construction, formulation of state space equations, and development of transitional matrices. It also involves transformation of multi‐state models into two‐state models (each comprises of an “up” state and a “down” state) through the use of the frequency and duration method for determining the failure and repair rates, as well as the mean‐time‐between‐failures (MTBF) of the entire tunnel. By using the proposed bottom‐up approach, a MTBF tree linking the availability measures of individual equipment with those of sub‐systems, and ultimately the whole tunnel can be developed.

The tunnel availability measures obtained by this analysis can be used in making comparisons between different tunnel designs so as to determine the value for money of various options. Furthermore, weaknesses in a tunnel design can be identified in the analysis. The information obtained from this method can also be used to evaluate adequacy, security and maintainability of a tunnel.

The reliability and maintainability of tunnel infrastructure and systems are crucial factors for ensuring safety of tunnel operation. Unsafe conditions will cause closure of a tunnel. Efforts to improve availability of a tunnel often increase the tunnel's construction cost. Due to the complexity of tunnel systems, it is difficult to compare different tunnel designs, and trade‐off analyses to strike a balance between target availability and construction cost of a tunnel design are seldom performed. This paper presents a systematic methodology to address these issues. This methodology allows tunnel management to evaluate the adequacy, security and maintainability of a tunnel so that design weaknesses can be identified and the value of design improvements can be determined. The methodology can also be used to evaluate designs of other complex systems such as power generation or petrochemical processing plants.

A worked example demonstrating the application of the proposed methodology is presented in this paper.

In this study, four sourcing strategies are identified in the delivery of maintenance service in facilities management, namely in‐sourcing, out‐tasking, outsourcing for cost saving, and outsourcing for capability. Since each of these strategies has merits under specific circumstances, a framework for the selection of appropriate sourcing strategy in particular situations is presented. This framework, which takes into consideration both the scope and purpose of the sourcing decision, was developed on the basis of results of earlier research and has been validated by the findings obtained from interviews with practitioners in exemplary organizations. This paper also provides guidelines for implementing the selected sourcing option, along with discussion of the related strategic and operational issues.

Performance measures should be linked to an organization’s strategy in order to provide useful information for making effective decisions and shaping desirable employee behaviour. The pitfalls relating to the indiscriminate use of common maintenance performance indicators are discussed in this paper. It also reviews four approaches to maintenance performance measures. The value‐based performance measure evaluates the impact of maintenance activities on the future value of the organization. The Balanced Scorecard (BSC) provides a framework for translating strategy into operational measures that collectively capture the critical requirements for sustaining the organization’s success. System audits are the tool for measuring organizational culture, which in turn determines the appropriate approach to the organization of maintenance functions. The operational efficiency of an organization’s maintenance function can be benchmarked with those of its counterparts in other organizations by using Data Envelopment Analysis (DEA). Among these approaches, the one which builds on the BSC embraces the design principles of a good performance measurement system. To smooth the adoption of the BSC approach to managing maintenance operations, a related research agenda is proposed in the concluding section.

Performance of the maintenance function is typically measured for operational control purposes. Since maintenance also has a strategic dimension, its performance measurement system should be linked to the espoused strategy of the function in order to get the maximum impact. This paper presents a structured approach to managing maintenance performance developed from this premise. The measurement system features a balanced scorecard (BSC) composed of key performance indicators (KPIs). The BSC is used to inform employees of the strategy pursued by the maintenance function, and to track the effectiveness of action plans in meeting the strategic objectives. The various steps involved in the process are also discussed.

The purpose of this paper is to explore whether or not a preventive replacement model always gives a solution with a specified preventive effect and looks at the relationship between the preventive effect and cost saving.

The age and block replacement policies with the Weibull failure distribution are considered. Measures of the preventive effect associated with specific maintenance policies are derived.

The sufficient condition to achieve a given preventive effect is represented graphically as a function of the system's aging intensity and the cost ratio of failure and preventive replacements.

The models developed in the paper will help maintenance engineers to know whether a system is aged or not and then they can make a decision on replacement.

The optimal replacement models considered in this paper give a solution with a good preventive effect only if the maintained system is sufficiently aged. The criterion whether or not the system is sufficiently aged is set by the decision‐maker based on specific maintenance situations or maintenance objectives.