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This paper discusses the concept, definition and usage of Key Activity Indicators (KAIs) and their integration within a Performance Measurement and Management system (PMM).

The actual definition and application areas of the KAIs are determined through a systematic literature review. Successively, a thorough definition of Key Activity Indicators is provided, along with a set of criteria for their deployment. Lastly, a case involving a Large Scale Retail Trade (LSRT) company is reported to report an example for guiding KAIs adoption.

This research shows that the scientific background concerning KAIs is still not mature. Moreover, the paper defines the role of KAIs for measuring operational activities and their possible connection with Key Performance Indicators (KPIs).

Although KAIs have been introduced and discussed in the scientific literature; there is no evidence of criteria to deploy these indicators, leaving organizations without any guidance for their operational implementation.

From an academic standpoint, the study provides an overview of the usage of KAIs within the present scientific contributions, showing the advancements of this research field. From an industrial standpoint, the research proposes a set of criteria for the organizational deployment of KAIs.

The study investigates the concept of KAIs that, besides being originally conceived within World Class Manufacturing (WCM), has not received much attention in the scientific literature.

The overall purpose of this study is to investigate impact of managerial characteristics on key performance indicators in the Kenyan hotel industry.

A cross‐sectional survey research design was used to gather primary data using self‐administered questionnaires. A sample of 160 hospitality managers was selected proportionately by simple random sample method from six hotels in Nairobi and Mombasa. A custom factorial univariate analysis of variance was used to analyze the data.

Hospitality managers in Kenya are still focusing on financial and result measures of performance while ignoring non‐financial and determinant measures. Managerial demographic characteristics; age, education, current position, functional area, and performance appraisal influence managers' choice of key performance indicators.

The model violated assumptions of homogeneity of variances. Literature review revealed a severe lack of Kenyan‐based research in tourism and hospitality industries on performance measurement practices hence the need for future research in this area.

The hotels need to invest in comprehensive performance management systems suitable for Kenyan hospitality industry that will incorporate both financial and non‐financial performance measures.

The study focuses on level of use of performance indicators and level of importance attached to performance indicators in the Kenyan hospitality industry. Managerial demographic characteristics influence on key performance indicators are examined in leading service industry in a growing economy thus contributing to a new body of knowledge in management literature in Africa.

Two case studies in health and safety management identified key performance indicators that reflected a company’s overall performance obtained from a full benchmarking audit. An intra‐company benchmarking audit, comparing operational health and safety management performance was completed within 12 semi‐autonomous subsidiaries of a large national food manufacturer. A significant (r = 0.985) positive relationship was obtained between ten operational performance indicators and overall performance. The key factors were found to have a common theme relating to employer‐employee openness in communication on health and safety issues. An inter‐company benchmarking audit comparing strategic health and safety management performance was completed within eight companies in the small, multi‐site retail sector. A significant (r = 0.988) positive relationship was obtained between ten strategic performance indicators and overall performance. The key factors did not have a common theme but there was evidence that integration of health and safety management into long‐term business decision making was a strong factor.

Building energy efficiency retrofit (BEER) not only provides excellent opportunities to reduce overall energy consumption of buildings in a city but also encourages environmental protection, the rational use of resources, and occupants' healthcare, which all contribute towards the sustainability of existing buildings. However, there is a lack of effective performance indicators to measure the sustainability of BEER projects. The aim of this paper is to formulate a list of key performance indicators (KPI) for the sustainability assessment of BEER in hotel buildings.

First, a literature review and in‐depth interviews with industry experts and academic researchers were conducted, which filtered the performance indicators for assessing sustainability. Second, a questionnaire survey was conducted to collect data from various groups of experts to analyze the significance of the selected performance indicators. Finally, a model based on fuzzy set theory was designed to identify the key performance indicators (KPIs) for the sustainability of BEER.

Eight KPIs were identified based on fuzzy set theory in this study. They are: quality performance, hotel energy management, cost performance, project profitability, energy consumption and resources saving, health and safety, stakeholder satisfaction, and innovation and improvement.

The KPIs of sustainability of BEER identified for hotel buildings in China in this study can be useful reference for other similar research. However, with the different requirements for building types and building ownerships, the KPIs of sustainability of BEER for different buildings may be variable. The findings in this study may not be directly relevant to other types of building.

Key performance indicators for the sustainability assessment of BEER in hotel buildings in China are identified and analyzed in this study. The KPIs can help decision‐makers to identify an optimal solution between alternatives, which presents the maximum sustainability performance.

A growing body of literature has begun in the direction of supply chain performance measurement. However, selecting the appropriate set of key performance indicators (KPIs) for measuring supply chain performance have always remained a challenge. The purpose of this paper is to identify the KPIs and categorize them specifically for measuring retail supply chain performance.

A qualitative approach, based on literature has been adopted. Published literature from refereed journals on supply chain performance measurement has been considered and various approaches for developing KPIs have been studied to develop a theoretical framework for performance measurement in retail supply chain.

The paper identifies key indicators for performance measurement and classifies them into four major categories: transport optimization, information technology optimization, inventory optimization and resource optimization. These key indicators are arranged precisely for retail industry. A theoretical framework is proposed to link the performance of these constructs on financial performance of the firm.

Future research can be carried out to validate the relevance and applicability of identified indicators. The study can be further conducted to measure the interrelationships between the KPIs and their impact on financial performance of the firm.

This study proposes a list of indicators for retail industry, which are presented in appropriate categories so that it can be used by the focussed teams for further improvement.

To the best of authors’ knowledge, no other study has categorized the KPIs into groups, specifically for measuring retail supply chain performance. The researcher also intends to carry out further empirical study to test the proposed theoretical framework.

The purpose of this paper is to introduce an alternative approach of measuring construction industry performance using maturity modeling. The focus is on introducing a newly developed maturity model referred to as the construction industry macro maturity model (CIM3) and highlighting its use by assessing the maturity of the construction industry of the Province of New Brunswick, Canada.

Current methods of construction industry performance measurement such as labor productivity and competitiveness are briefly reviewed, highlighting their weaknesses. The theoretical underpinnings of the CIM3 are discussed and the implementation of the CIM3 to measure the cost and quality management maturity of the New Brunswick construction industry is presented.

An assessment of the construction industry's maturity using the CIM3 provides a leading indication of performance. This is based on the industry being structured according to key practices areas that contain key practices. The industry's key practices are linked to objectives that lead to the achievement of performance goals. The maturity of the construction industry with respect to its key practices is a function of the relative importance of the key practices and the capabilities of the industry in implementing the key practices. Based on this, the implementation of the CIM3 in New Brunswick found that the NB construction industry is more mature in cost management than in quality management.

This paper contributes to the existing body of knowledge on industry performance measurement, and more particularly, construction industry performance measurement. The concept of maturity modeling applied here promotes and demonstrates the use of leading indicators of performance, as recommended in most performance measurement literature.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

This study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.

The study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.

Empirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.

Apart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.

The uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

本研究旨在探討與通貨膨脹有關的狀況的組成部分(通脹預期 、通脹不確定性及體現了的通脹), 宏觀經濟不確定性及經濟衰退狀況的可能性、在一段特定時間內對美國銀行業的表現指數有何種程度的影響。

研究採用塞爾納 (Zellner) (1962) 提出的看似無關迴歸模型 (SUR)，去探討通脹狀況的特定組成部分及其它不利的宏觀經濟狀況如何影響美國銀行業內的績效動態。

實證證據暗示在被研究的各個不利宏觀經濟狀況中，通脹預期及宏觀經濟不確定性，對美國銀行業內的主要業績指標的約束影響, 與其它被探討的狀況相比，往往會較重大。相對地、本研究結果顯示通脹預期及宏觀經濟不確定性，對美國銀行業資本回報率的約束影響、往往遠多於資產收益率。研究結果進一步顯示，在被探討的三個銀行業績指標中，就本研究所探討的各個不利的宏觀經濟狀況而言，淨息差是脆弱性最小的銀行業績指標。

除了上述各實證結果外，本研究結果預期會給銀行業內機構間作戰略規劃的決定時提供資料，譬如，各項研究結果或可在制定旨在減少與特定業績指標如資本回報率相聯繫的脆弱性的政策和經營策略時提供資料。這脆弱性的減少，是透過嚴謹地研究各個業績指標，如何對在本研究中被探討的個別不利宏觀經濟狀況作出反應而達致的。這程序或許最終會幫助建立一個以減少各個不利宏觀經濟狀況對主要業績指標的影響為目的的量身定制措施／程序。本研究的結果，或許亦可為更多旨在減弱眾所周知的宏觀經濟狀況對銀行業運營效率的影響的適應性政策提供平台。

與文獻中可見的相關研究比較，本研究的獨特性源於其實證分析，是涉及在同一個構架內處理宏觀經濟狀況相互有關的組成部分的三個變體 (通脹狀況的不同變體) 。

The purpose of this paper is to provide an overview of research and development in the measurement of maintenance performance. It considers the problems of various measuring parameters and comments on the lack of structure in and references for the measurement of maintenance performance. The main focus is to determine how value can be created for organizations by measuring maintenance performance, examining such maintenance strategies as condition‐based maintenance, reliability‐centred maintenance, e‐maintenance, etc. In other words, the objectives are to find frameworks or models that can be used to evaluate different maintenance strategies and determine the value of these frameworks for an organization.

A state‐of‐the‐art literature review has been carried out to answer the following two research questions. First, what approaches and techniques are used for maintenance performance measurement (MPM) and which MPM techniques are optimal for evaluating maintenance strategies? Second, in general, how can MPM create value for organizations and, more specifically, which system of measurement is best for which maintenance strategy?

The body of knowledge on maintenance performance is both quantitatively and qualitatively based. Quantitative approaches include economic and technical ratios, value‐based and balanced scorecards, system audits, composite formulations, and statistical and partial maintenance productivity indices. Qualitative approaches include human factors, amongst other aspects. Qualitatively based approaches are adopted because of the inherent limitations of effectively measuring a complex function such as maintenance through quantitative models. Maintenance decision makers often come to the best conclusion using heuristics, backed up by qualitative assessment, supported by quantitative measures. Both maintenance performance perspectives are included in this overview.

A comprehensive review of maintenance performance metrics is offered, aiming to give, in a condensed form, an extensive introduction to MPM and a presentation of the state of the art in this field.

The purpose of this paper is to identify key variables that affect the quantifiable key performance indicators (KPIs) and to derive equations to measure these indicators. Qualitative KPIs are also discussed in terms of the aspects that need to be covered while carrying out qualitative performance assessment.

A combination of literature and an industry opinion-based qualitative approach is applied to develop equations to calculate the quantifiable KPIs. A facility asset management consulting firm is included in the process of deriving the equations. Key aspects of a facility's qualitative performance assessment are categorized and discussed by performing a literature review.

Mathematical expressions for core performance indicators are presented and discussed along with key variables. In addition, the information needed to quantify these core indicators is also discussed.

This paper represents the second step towards establishment of a relevant list of quantifiable and measurable core KPIs, which were identified and categorized in Part I of this paper. In Part II, the authors derive equations to quantify the core KPIs. Future research is needed to use relevant information from industry for validating these equations.

A need for a concise and relevant list of KPIs was identified in Part I of this paper. Part II provides an approach to quantify the core KPIs based on information that is available in the industry. This research will help facility management professionals in not only selecting the indicators of choice, but also quantifying them based on available information yielding enhanced facility management decisions with measurable facility performance outcomes.

This paper provides equations and variables to measure a facility's physical, functional and financial performance using both quantitative and qualitative performance assessments.