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The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

Project managers rely on control strategies to deliver excellent outputs. However, little is known about how clients' project managers select control strategies in projects which are knowledge-intensive and have intangible outputs. This study aims to examine how clients' project managers select project control strategies in professional service projects.

A questionnaire survey of 360 architectural and engineering (A/E) design projects was adopted. Data were analyzed through the hierarchical regression.

Both clients' knowledge of measuring outcomes and process uncertainty give rise to their project managers setting up behavior and social controls. Level of process uncertainty positively moderates the impact of client's knowledge of measuring outcomes on outcome control.

This study mainly examined the client's knowledge of measuring outcomes and process uncertainties. Future studies could be conducted to expand the scope by including other contextual factors, for instance market and regulatory factors.

From the client side, if they want to simultaneously adopt outcome, behavior and social controls, they would need to increase their knowledge of measuring outcomes by adopting established assessment tools or appointing a third party to assist in design outcome evaluation.

This study contributes to the body of knowledge by showing that the level of intangibility of project outputs influences the types of control system which project managers adopt.

The purpose of this paper is to provide a comprehensive review of a non-contact full-field optical measurement technique known as digital image correlation (DIC).

The approach of this review paper is to introduce the research pertaining to DIC. It comprehensively covers crucial facets including its principles, historical development, core challenges, current research status and practical applications. Additionally, it delves into unresolved issues and outlines future research objectives.

The findings of this review encompass essential aspects of DIC, including core issues like the subpixel registration algorithm, camera calibration, measurement of surface deformation in 3D complex structures and applications in ultra-high-temperature settings. Additionally, the review presents the prevailing strategies for addressing these challenges, the most recent advancements in DIC applications across quasi-static, dynamic, ultra-high-temperature, large-scale and micro-scale engineering domains, along with key directions for future research endeavors.

This review holds a substantial value as it furnishes a comprehensive and in-depth introduction to DIC, while also spotlighting its prospective applications.

This study aims to explore which outcome measures are used by occupational therapy staff in adult social care settings in the UK, and the factors affecting use of outcome measures.

A quantitative descriptive research design was used, using a cross-sectional study to explore occupational therapy staff views on the use of outcome measures. A 38-question survey was developed on Microsoft Forms. Recruitment occurred online over a three-week period in 2021 via the social media platform “Twitter”. Results were analysed using Excel using descriptive statistics and qualitative results used thematic analysis.

Participants (n = 20) used a range of outcome measures (13) in adult social care settings in the previous 12 months. Standardised measures were used by half the sample in the previous 12 months. The Therapy Outcome Measure and Barthel Index were in most use. The breadth of adult social care practice and practical factors such as caseload and lack of a meaningful tool were found to be barriers to outcome measure use. Facilitators included service improvement, accountability, use of audit and professional occupational therapy leadership.

The overall use of outcome measures can be considered low in this setting, with manager support seen to be key to the use of outcome measures. Further research is needed to investigate nationwide use.

Training, time and manager support are key to use of standardised tests and outcome measures in the adult social care settings. The use of occupational performance measures should be considered to demonstrate unique professional impact.

This contemporary study reveals use of outcome measures within occupational therapy adult social care services in the UK, which is an under researched and under published area.

Financing remains a serious concern for firms and is considered the main hurdle in the growth and development of small and medium enterprises (SMEs). Recently, a new stream of financing (SCF; supply chain finance) has emerged to meet the financing issues of SMEs. Therefore, measuring SCF is essential to support SMEs’ operations. This study aims to develop and validate the SCF scale based on extant literature.

Using a mixed-method approach, this study recruited different samples of SME entrepreneurs to confirm the internal consistency, assess construct validity and check the item structure of the SCF scale in AMOS.

The outcomes of confirmatory factor analysis demonstrated the six factors of SCF (inventory financing, working capital optimization, reverse financing, fixed assets financing, logistics financing and order cycle financing) spread over 21 items. An interitem solid structure of the SCF scale offers invaluable contributions to the supply chain management literature.

This research supports SME entrepreneurs to obtain secure financing at the best cost, mitigating the risk of default, supporting the buyers’ payment terms, providing early payment to suppliers and strengthening the firm’s value chains. SMEs can obtain financing per their requirements to support their operational business processes. Moreover, SMEs can plan, manage and control finance-related transactional activities by correctly identifying financing solutions.

The present study contributes to SCM literature by developing and validating the SCF scale. To the best of the author’s knowledge, this is the first study that redefined SCF and identified its six dimensions.

This study aims to investigate the growing use of financial metrics (such as return on investment [ROI]) to measure performance and evaluate human capital (HC) investments.

The research employed an embedded case study approach, examining how one ROI approach was applied to evaluating HC investments, across three sectors (corporate, public health and international development).

Three major findings emerged in this study: First, interpretations of ROI can lead to ambiguity during implementation. ROI is interpreted trichotomously – metaphorically, as a desire for value; literally, as a metric; and procedurally, as a method for planning and evaluating HC investments. Second, understanding, measuring and tracking the domains of people performance (cognitive, affective and psychomotor) is vital to evaluating the impact of HC investments because this is where the change in behavior occurs. Third, although the logic model measures the change in process following an intervention (input-activity-output-outcome-impact), other approaches measure the change in behavior of people in the intervention (people performance).

These findings provide clarity for practitioners about challenges when applying ROI.

This is the first study to explore how the ROI financial metric is applied in a new domain by first examining its interpretation. It elucidates the use of ROI in practice, as well as the different purposes of key ROI approaches.

Women's participation in the workforce and in managerial positions, which has led to greater diversity, reconstructs professional perceptions and preferences. The purpose of this research is to examine “Work Outcome Preferences” among men and women according to organizational status and the impact of other demographic factors.

The Meaning of Work (MOW) questionnaire was filled by 1,161 men and women employees in organizations: 744 workers, 256 junior managers and 161 middle managers. To examine the hypotheses, authors conducted an analysis of variance (ANOVA) test and a linear regression analysis for women and men.

The gender differences regarding work outcomes preferences decreases with career promotion. Further, the higher the organizational status, the higher the need for interesting and satisfying work among both men and women. Among women, the higher the organizational status, the higher the need for status and prestige and for serving society and the lower the need for interpersonal contacts and income.

Better understanding of the preferred outcomes among women and men in the three organizational statuses and the impact of promotion and varied demographic variables can help in the planning of material and non-material reward systems and methods suitable to the different sub-groups.

As far as authors know, there is not a single study focusing on the differences between narrow career stages such as workers, junior and middle managers according to gender regarding work values/work outcome preferences.

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.

While, supply chain resilience (SCRES) continues to be a dominant topic in both academic and business literature and has gained more attention recently, there is limited knowledge on SCRES capabilities specific to business functions. The purpose of this paper is to identify and investigate capabilities shared between supply, operations and logistics that are most important for SCRES.

To address this gap, the authors followed a multi-method research approach. First, the authors used the grounded theory method to generate a theoretical framework based on interviews with 51 managers from five companies in automotive SCs. Next, the authors empirically validated the framework using a survey of 340 SC professionals from the manufacturing industry.

Five significant capabilities emerged from the qualitative study; all were significant in empirical validation. This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES.

This research advances the knowledge of SCRES as it informs managerial decision-making by identifying capabilities common to supply, logistics and operations that impact SCRES. In addition, the findings of this research help managers better allocate resources among significant capabilities.