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For many years management accountants have been involved in the design of information systems for decision-making. To be effective in system design, accountants need pertinent and reliable performance measures within a valid framework. The Balanced Scorecard (BSC) has received a great deal of attention as a comprehensive model of performance that takes into account both financial and non-financial measures. This paper examines the empirical reliability and validity of the BSC framework and its associated measures. With reference to content validity, internal consistency reliability, and factorial validity, results show that BSC, with measures grouped into its four dimensions, is a valid performance model.

Previous studies have called for better reliability and validity of BSC measures. The present study may help in the design and implementation of BSCs in business units by adding robustness to the BSC framework, and by suggesting a set of valid measures associated with the four BSC dimensions. The results may lead to reduced costs of BSC design and implementation, and enhanced consistency of future studies of the BSC.

A majority of products for manufacturing or consumers have multiple characteristics that must meet the requirements of the customer. For example, a steel beam any have dimensional tolerances on its length, width, or height and functional tolerances on its strength. The characteristics are influenced by different processes that create the product. For an individual characteristic, process capability measures exist that convey the degree to which the characteristic meets the specification requirements. Such measures may indicate the proportion of nonconforming product related to the particular characteristic, under some distributional assumptions of the characteristic. For products with multiple characteristics, the unit costs of rectification may be different, making the satisfaction of some characteristics meeting customer requirements more important than others. In this paper, an aggregate process capability performance measure is developed that considers the relative importance of the characteristic based on unit costs of nonconformance. Based on the aggregate measure, appropriate process capability measures for the individual measures are also derived. Bounds on the aggregate capability measures are also established.

Amidst the complicated nature of the UAE’s facilities management (FM) industry, the need to recalibrate the existing performance measurement (PM) system measures and criteria has been resonating to ensure their ability to capture the FM industry trends and dynamics, thus enhancing organizational excellence. Therefore, this research aimed to propose a specific PM tool to the country’s FM industry to accurately assess performance and establish strategic enhancements.

The study reviewed literature on the available PM systems to gather the available measures, which were presented to a focus group of seven participants, who were purposively selected based on their expertise in FM and PM implementation in the UAE to adjust them and add ones relevant to the UAE’s FM industry.

The focus group conducted various changes, from retaining certain measures and criteria, renaming them to simplify or make them more representative of the industry, ranking them based on their importance to limit their numbers, to finally categorizing them as enablers or results. Consequently, the final proposed tool was composed of nine dimensions with 51 measures as performance enablers and three dimensions with 11 measures as performance results. Seven measures were added by the experts, who highlighted their increasing popularity in the UAE’s FM industry.

Through addressing the critical void in literature, this paper develops a specific PM tool aligning with the intricacy of the UAE’s FM industry, thus providing proactive contribution to the industry’s effective and sustainable growth.

To date, to the best of the authors’ knowledge, the use of implicit measures in the service research domain is limited. This paper aims to introduce implicit measures and explain why, or for what purpose, they are worthwhile to consider; how these measures can be used; and when and where implicit measures merit the service researcher’s consideration.

To gain an understanding of how implicit measures could benefit service research, three promising implicit measures are discussed, namely, the implicit association test, the affect misattribution procedure and the propositional evaluation paradigm. More specifically, this paper delves into how implicit measures can support service research, focusing on three focal service topics, namely, technology, affective processes including customer experience and service employees.

This paper demonstrates how implicit measures can investigate paramount service-related subjects. Additionally, it provides essential methodological “need-to-knows” for assessing others’ work with implicit measures and/or for starting your own use of them.

This paper introduces when and why to consider integrating implicit measures in service research, along with a roadmap on how to get started.

This study developed new measures of the routine and non-routine task contents of managerial, professional, technical, and clerical occupations from a workload perspective. Here, we present a comparative analysis of the workload structures of state and industrial sector employees.

Our method involves detailed descriptions of work processes and an element-wise time study. We collected and analysed data to obtain a workload structure that falls within three conceptual task categories: (i) non-routine analytic tasks, (ii) non-routine interactive tasks and (iii) routine cognitive tasks. A total of 2,312 state and industrial sector employees in Kazakhstan participated in the study. The data were collected using a proprietary web application that resembles a timesheet.

The study results are consistent with the general trend reported by previous studies: the higher the job level, the lower the occupation’s routine task content. In addition, the routine cognitive task contents of managerial, professional, technical, and clerical occupations in the industrial sector are higher than those in local governments. The work of women is also more routinary than that of men. Finally, vthe routine cognitive task contents of occupations in administrative units are higher than those of occupations in substantive units.

Our study sought to address the challenges of using the task-based approach associated with measuring tasks by introducing a new measurement framework. The main advantage of our task measures is a direct approach to assessing workloads consisting of routine tasks, which allows for an accurate estimation of potential staff reductions due to the automation of work processes.

The purpose of this review is to evaluate existing learning agility measures and offer recommendations for their use in organizational and scholarly contexts.

This is a general review paper assessing the psychometric qualities of prevalent learning agility measures. Measures were selected based on their predominance and use in the learning agility literature and organizational settings.

Learning agility measurement is an area requiring further research. Multiple conceptualizations of learning agility exist, making the true structure of learning agility unclear. The learning agility measures in the academic literature deviate from learning agility’s traditional conceptualization and require further validation and convergent validity studies. Commercial measures of learning agility exist, but their development procedures are not subjected to peer review and are not widely used in academic research, given the cost associated with their use.

Learning agility is prevalently used in organizational settings and is receiving increased scholarly attention. Various conceptualizations and measurement tools exist, and it is unclear how these theories and measures relate and differ. This paper contributes to practice by providing practical guidelines and limitations for measuring learning agility.

Learning agility was initially conceived as a multidimensional construct comprising people agility, results agility, change agility and mental agility. As the construct has evolved, the dimension structure of the measure has evolved as well. This study addresses a gap in our current understanding of how to conceptualize and measure learning agility.

This paper aims to examine the impact of the assurance and advisory role of internal audit (ADRIA) on organisational, human and technical proactive measures to enhance cybersecurity (CS).

The questionnaire was used to collect data for 97 internal auditors (IAu) from the Gulf Cooperation Council countries. The authors used partial least squares (PLS) to test the hypotheses.

The results show a positive effect of the ADRIA on each of the organisational proactive measures, human proactive measures and technical proactive measures to enhance CS. The study also found a positive effect of the confirmatory role of IA on both human proactive measures and technical proactive measures to enhance CS. No effect of the confirmatory role of IA on the organisational proactive measures is found.

This study focused on only three proactive measures to enhance CS, and this study was limited to the opinions of IAu. In addition, the study was limited to using regression analysis according to the PLS method.

The results of this study show that managers need to consider the influential role of IA as a value-adding activity in reducing CS risks and activating proactive measures. Also, IAu must expand its capabilities, skills and knowledge in CS auditing to provide a bold view of cyber threats. At the same time, the institutions responsible for preparing IA standards should develop standards and guidelines that help IAu to play assurance and advisory roles.

To the best of the authors’ knowledge, this is the first study of its kind that deals with the impact of the assurance and ADRIA on proactive measures to enhance CS. In addition, the study determines the nature of the advisory role and the assurance role of IA to strengthen CS.

The main purpose of this paper was to evaluate the validation process of food safety control measures.

The validation of control measures has been analyzed at 50 food companies in Serbia. The sample included companies that produce food of both plant and animal origin and have certified food safety management systems. A total of 156 control measures that combat physical hazards (41.6%), followed by microbial hazards (34.0%) and chemical hazards (24.4%), have been analyzed. To enable quantification of the validation protocols, each control measure was assigned a score.

The validation scores showed that the highest level of validation was observed in large companies, as opposed to small and medium-sized companies (p < 0.05). The type of food safety hazards and the food sector did not reveal any statistical differences in-between the scores. The main approach to validating control measures was referring to the technical documentation of equipment used (52.6%), followed by scientific and legal requirements (30.7%). Less than 20% of the analyzed control measures were validated with operational data collected on-site. No mathematical modeling was observed for the sampled food companies. Future steps should include the development of validation guides for different types of control measures and training modules.

This study can serve as an improvement guide for food safety consultants, food safety auditors, certification bodies, inspection services, food technologists and food managers.

This study is one of the first to provide an insight into how food companies validate their control measures to combat microbial, chemical and physical food safety hazards.

This paper aims to (1) identify the different performance drivers (lead indicators) and outcome measures (lag indicators) investigated in the literature concerning the four balanced scorecard (BSC) perspectives in operations management (OM) contexts and (2) understand how performance drivers and outcome measures (and substantiated perspectives) are related.

We undertake a systematic literature review of the BSC literature in OM journals. From the final sample of 40 articles, performance drivers and outcome measures have been identified, and the relationships amongst them have been synthesised according to the system dynamics approach.

Findings show (1) the most relevant performance drivers and outcome measures within each BSC perspective, (2) their relationships, (3) how the perspectives are linked through the performance drivers and outcome measures and (4) how the different measures relate systemically. Accordingly, four causal loops amongst identified measures have been built, which – jointly considered – allowed for the creation of a dynamic strategy map for OM.

This study is the first one that provides a comprehensive and holistic view of how the different performance drivers and outcome measures within and between the four BSC perspectives in OM relate systemically, increasing the knowledge and understanding of scholars and practitioners.

This study proposes a novel measure for management’s horizon (short-termism or myopia vs long-termism or hyperopia) derived from easily obtainable firm-level accounting and stock market performance data. The authors use the measure to explore the impact of managements’ horizon on firms’ investment efficiency.

The authors rely on two commonly used but uncorrelated measures of management performance: accounting performance (return on capital employed, ROCE) and stock market performance (average abnormal return, AAR). The authors combine these measures to develop a multidimensional framework for performance, which classifies firms into four groups: efficient (high accounting and high market performance), poor (low accounting and low market performance), myopic (high accounting and low market performance) and hyperopic (low accounting and high market performance). The authors validate this framework and deploy it to explore the relationship between horizon and firms’ investment efficiency.

In validation tests, the authors show that management myopia (hyperopia) explains firms’ decision to cut (grow) research and development investments. Further, as expected, myopic (hyperopic) firms are associated with significantly more (less) accrual and real earnings management. The empirical tests on the link between horizon and investment efficiency suggest that myopic managers cut new investments while their hyperopic counterparts grow the same. Ultimately, the authors find that myopia (hyperopia) exacerbates(mitigates) the over-investment of free cash flow problem.

The authors introduce a framework for assessing management’s horizon using easily obtainable measures of performance. The framework explains inconsistencies in prior empirical research using different measures of performance (accounting versus market). The authors demonstrate its utility by showing that the measure explains decisions around research and development investment, earnings management and firm investments.