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This paper aims to describe an interdisciplinary and innovative research conducted in Switzerland, at the Geneva School of Business Administration HES-SO and supported by the State Archives of Neuchâtel (Office des archives de l'État de Neuchâtel, OAEN). The problem to be addressed is one of the most classical ones: how to extract and discriminate relevant data in a huge amount of diversified and complex data record formats and contents. The goal of this study is to provide a framework and a proof of concept for a software that helps taking defensible decisions on the retention and disposal of records and data proposed to the OAEN. For this purpose, the authors designed two axes: the archival axis, to propose archival metrics for the appraisal of structured and unstructured data, and the data mining axis to propose algorithmic methods as complementary or/and additional metrics for the appraisal process.

Based on two axes, this exploratory study designs and tests the feasibility of archival metrics that are paired to data mining metrics, to advance, as much as possible, the digital appraisal process in a systematic or even automatic way. Under Axis 1, the authors have initiated three steps: first, the design of a conceptual framework to records data appraisal with a detailed three-dimensional approach (trustworthiness, exploitability, representativeness). In addition, the authors defined the main principles and postulates to guide the operationalization of the conceptual dimensions. Second, the operationalization proposed metrics expressed in terms of variables supported by a quantitative method for their measurement and scoring. Third, the authors shared this conceptual framework proposing the dimensions and operationalized variables (metrics) with experienced professionals to validate them. The expert’s feedback finally gave the authors an idea on: the relevance and the feasibility of these metrics. Those two aspects may demonstrate the acceptability of such method in a real-life archival practice. In parallel, Axis 2 proposes functionalities to cover not only macro analysis for data but also the algorithmic methods to enable the computation of digital archival and data mining metrics. Based on that, three use cases were proposed to imagine plausible and illustrative scenarios for the application of such a solution.

The main results demonstrate the feasibility of measuring the value of data and records with a reproducible method. More specifically, for Axis 1, the authors applied the metrics in a flexible and modular way. The authors defined also the main principles needed to enable computational scoring method. The results obtained through the expert’s consultation on the relevance of 42 metrics indicate an acceptance rate above 80%. In addition, the results show that 60% of all metrics can be automated. Regarding Axis 2, 33 functionalities were developed and proposed under six main types: macro analysis, microanalysis, statistics, retrieval, administration and, finally, the decision modeling and machine learning. The relevance of metrics and functionalities is based on the theoretical validity and computational character of their method. These results are largely satisfactory and promising.

This study offers a valuable aid to improve the validity and performance of archival appraisal processes and decision-making. Transferability and applicability of these archival and data mining metrics could be considered for other types of data. An adaptation of this method and its metrics could be tested on research data, medical data or banking data.

The purpose of the present analysis is to show that HR systems are not always designed in ways that consider the well‐being of employees. In particular, performance metric methods seem to be designed with organizational goals in mind while focusing less on what employees need and desire.

A literature review and multiple case‐study method was utilized.

The analysis showed that performance metrics should be revaluated by executives and HR professionals if they seek to develop socially responsible organizational cultures which care about the well‐being of employees.

The paper exposes the fact that performance appraisal techniques can be rooted in methodologies that ignore or deemphasize the value of employee well‐being. The analysis provides a context in which all HR practices can be questioned in relation to meeting the standards of a social justice agenda in the area of corporate social responsibility.

The core business of universities is learning. Cognitive thinking is critical for learning and the development of new knowledge which are essential in higher education. Creative, reflective and critical thinking are negatively affected by unrealistic demands and stress. The purpose of this paper is to argue that key performance indicators (KPIs) and performance management are detrimental in the higher education sector, as they cause undue stress which impacts negatively on an essential criterion of academia, cognitive thinking.

To explore this issue, the authors discuss the impact of stressful demands in the context of Australian higher education. The paper draws on literature that describes managerialism and on neuroscientific evidence to develop a hypothesis that supports a more holistic approach to human resources management of academics.

Performance management and measures (including KPIs) add to the complex demands of academic work despite a lack of evidence that they are appropriate in the higher education sector.

Performance management systems and KPIs undermine creative, reflective and critical thinking. Principles governing education should supersede the ever-growing emphasis that is being placed on quantitative measures and bureaucratic demands in higher education.

The purpose of this paper is to demonstrate the need for and propose a more aligned and integrated standard for performance evaluation to enhance effective strategic control.

The paper reviews the various issues creating discontent with the performance appraisal systems within many organizations and demonstrates how these problems inhibit successful strategic control. It attempts to cogently incorporate the performance appraisal characteristics needed for the exercise to function as a critical organizational control metric and a useful feedback mechanism for strategic management of the firm.

The paper finds that, whereas performance evaluation has received reasonably robust examination in the human resources literature, explicit guidance toward the integration with strategic control is inadequate. Without consistent alignment between these functions, however, performance appraisal becomes an exercise in futility instead of a vital control measurement, often resulting in not only personnel dissatisfaction, but also, more importantly, an impediment to systematic strategy implementation.

The paper offers a viewpoint based upon the authors' experiences and a review of the literature. It aims to stimulate a broader understanding and discussion of the crucial link between performance evaluation and strategic control.

Although it is possible to theoretically separate the human resource function of performance appraisal from broader strategic management processes, such an approach is not realistic for organizational leaders charged with strategy execution. These leaders would benefit from a framework for ensuring this important HR function also meets the requirements for operative strategic control.

While many in the literature have focused on how to conduct legal and efficient performance evaluations, guidance on crafting such appraisals as control metrics is insufficient. The paper endeavors to provide this direction.

Robotic process automation (RPA) has recently emerged as a technology focusing on the automation of repetitive, frequent, voluminous and rule-based tasks. Despite a few practical examples that document successful RPA deployments in organizations, evidence of its economic benefits has been mostly anecdotal. The purpose of this paper is to present a step-by-step method to RPA investment appraisal and a business case demonstrating how the steps can be applied to practice.

The methodology relies on design science research (DSR). The step-by-step method is a design artefact that builds on the mapping of processes and modelling of the associated costs. Due to the longitudinal nature of capital investments, modelling uses discounted cashflow and present value methods. Empirical grounding characteristic to DSR is achieved by field testing the artefact.

The step-by-step method is comprised of a preparatory step, three modelling steps and a concluding step. The modelling consists of compounding the interest rate, discounting the investment costs and establishing measures for comparison. These steps were applied to seven business processes to be automated by the case company, Estate Blend. The decision to deploy RPA was found to be trivial, not only based on the initial case data, but also based on multiple sensitivity analyses that showed how resistant RPA investments are to changing circumstances.

By following the provided step-by-step method, executives and managers can quantify the costs and benefits of RPA. The developed method enables any organization to directly compare investment alternatives against each other and against the probable status quo where many tasks in organizations are still carried out manually with little to no automation.

The paper addresses a growing new domain in the field of business process management by capitalizing on DSR and modelling-based approaches to RPA investment appraisal.

The purpose of this paper is to propose an integrated framework to simultaneously identify and improve healthcare processes that are important from the healthcare provider's and patient's perspectives.

A modified quality function deployment (QFD) chart is introduced to the field of healthcare quality assurance. A healthcare service example is used to demonstrate the utility of the proposed chart.

The proposed framework is versatile and can be used in a wide variety of healthcare quality improvement contexts, wherein, two different perspectives are needed to be considered for identifying and improving critical healthcare processes.

The modified QFD chart used in conjunction with the stacked Pareto chart will facilitate the identification of key performance metrics from the patient's and the hospital's perspectives. Subsequently, the chief contributory factors at different levels are identified in a very efficient manner.

Healthcare quality improvement professionals will be able to use the proposed modified QFD chart in association with stacked Pareto chart for effective quality assurance.

The purpose of this case study is to describe how a global financial organization's corporate HR function, in partnership with divisional HR functions, increased the impact of HR initiatives through the development of an integrated and benchmarked metrics framework.

The methodology used to create the framework was a mixture of analytical deskwork, consultative enquiry and benchmarking.

To date many HR initiatives have failed to be taken seriously in the boardroom, and this is, in significant part, due to the lack of quantifiable impact measures. The initiative described here is a framework of metrics that can be used to monitor, track and evaluate the strategic impact of HR strategy.

The paper adds value to the practitioner community by offering up a process for the development of a metrics framework against which HR strategy can be evaluated and developed over time.

This study aims to propose a holistic model to rank and evaluate researchers’ performance. This holistic model is developed by focusing on brand equity, which includes three components of perceived quality, brand image and brand loyalty.

To show how the model works, two pseudo cases are presented.

This model encourages researchers to conduct more interdisciplinary research and collaborate with researchers from diverse backgrounds. Because the model includes publication attributes identified by researchers in the publication processes, it allows researchers to strengthen their brand equity score or performance.

The model is applicable not only to the fields of hospitality and tourism but also to other disciplines.

As one of the first studies in the field, this research introduces a holistic model to rank and evaluate researchers’ performance.

Human resource development (HRD) has been considered in enhancing organisational operations as human resources are vital for organisational performance. This study aims to examine the role of HRD on the effectiveness of public procurement in Tanzania.

This study employed a cross-sectional research design under which data was collected from 168 procurement professionals in Dodoma city, Tanzania. Structural equation modelling (SEM) was employed to analyse the collected data and examine the structural relationships between HRD and the effectiveness of public procurement in Tanzania.

The findings revealed that all the variables of human resource development; career development, training and performance appraisal, are statistically significant and positively related to the effectiveness of public procurement. Therefore, the findings reveal that career development, training and performance appraisal as HRD practices play an important role in enhancing the effectiveness of public procurement in the surveyed public procuring organisations in Tanzania.

This current study divides HRD into three main practices: career development, training and performance appraisal. This limits the study's applicability to other HRD practices that organisations may institutionalize to public procurement professionals who work in various public organisations in Tanzania.

This paper integrates the concept of HRD and public procurement effectiveness. Therefore, the study adds value to the literature on human resource management and public procurement management.