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This paper aims to propose a new metric, called the Research Productivity Index (RPI), which can be used to measure universities’ research productivity and benchmark them accordingly at both national and global levels.

The paper used a partial-factor productivity measurement as the basis to develop RPI, which considers the ratio of total weighted publications (outputs) to the used input (affiliated researchers). To demonstrate the applicability of the RPI, data were collected from Scopus to assess the research productivity of a university in the UAE, as an example. The methodological steps (algorithm) were demonstrated using mathematical and query functions to extract the required data from the Scopus data set and then compute the RPI value.

A new effective and objective metric was developed for measuring universities’ research productivity.

This paper suggests that Scopus could use RPI as a metric for measuring the research productivity of each university. RPI can be used by university administrators and government decision-makers to evaluate and rank/benchmark institutions’ research productivity. They can consequently make more effective decisions with regard to the efficient allocation of research budgets and funding.

This paper distinguishes between measuring research impact and research productivity. It proposes RPI for measuring the latter, whereas most existing metrics measure the former. RPI is an objective measurement, as it is calculated based on a constant period of time, three years, and takes into consideration the university size (i.e. affiliated researchers) in addition to the quality and quantity (total) of research outcomes.

The structure of the economy continues to change; where once they are dependent on the productivity of a manual workforce, companies increasingly depend on the productivity of knowledge workers. Today, knowledge workers account for more than two‐thirds of the workforce, and thus should be the focus of strategic plans to improve productivity. Currently there are no universally accepted methods to measure knowledge worker productivity, or even generally accepted categories. This paper provides a taxonomy of knowledge worker productivity measurements, and identifies a number of productivity dimensions that are used to categorize the findings of previous research. Also describes the relative density of discussions along these dimensions and identifies critical areas for future research.

The purpose of this literature review is to investigate the reliability of self-evaluation as a method for measuring the effect(s) of indoor environment quality (IEQ) on the productivity of office workers. The aim of this review is to identify the various constraints to its adequacy in measuring productivity.

Thirty studies were selected from peer-reviewed sources and reviewed on their method of measuring productivity. These studies used self-evaluation (questionnaires or interview) as the sole method of measuring the effect of IEQ on productivity/performance.

This review provides insight on the insufficiencies and biases prevalent in self-evaluation. Various issues that compromised the reliability of self-evaluation results in an office environment were discussed. It was concluded that self-evaluation is not reliable and does not accurately measure occupant productivity.

This study has been a review of past studies and their findings. Further studies that will provide empirical evidence are required to solely test the reliability of self-evaluation in measuring productivity and the effect of factors such as IEQ on it.

The paper calls for further debate on occupant productivity measurement and how the various factors that affect it can be quantified into measurable entities.

This paper fulfils an identified need to revisit the technique of self-evaluation as a method for measuring occupant productivity.

The purpose of this study is to identify methods appropriate for measuring the direct productivity of facilities management (FM) with respect to the providers, on both the industry level and the firm level.

This is a literature survey and conceptual analysis.

Prior studies are dominated by subjective assessments of how the office environment affects individual labour productivity. While the available EU data on productivity growth for the FM industry indicate a negative trend, they might be misleading. More recent research on the productivity of business services providers could be applied to the measurement of the productivity of FM firms. Co-production and effects of client satisfaction are important issues for measurement.

The analysis is concentrated on the direct productivity of FM providers. There is a need to develop objective measures of provider productivity, and there is a particular challenge in measuring how FM clients contribute to the productivity of FM providers.

Providers of FM services should be able to assess the efficiency of their resource use more clearly and to balance user satisfaction against resource use more efficiently.

The effects of co-production with clients need to be recognised, considering productivity effects on both providers and clients jointly. Sustainability is an argument for an increased focus on resource use in FM.

This is the first overview of issues raised when measuring the direct productivity of FM itself rather than indirect FM effects on office worker labour productivity.

Currently over seventy percent of the work force is employed in white‐collar jobs. The implication ofwhite‐collar productivity for organizational growth and competitiveness is extremely significant. It is easy to measure the productivity for blue‐collar employees, as the inputs and outputs are well defined. However the process of measuring the productivity of the white‐collar employee is complicated. A model for measuring white‐collar productivity is presented. The organization should design its own productivity measures seeking active employee involvement. The measures developed should be used to design productivity improvement strategies for long term growth and competitiveness of the organization.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.

The purpose of this paper is to measure service productivity using the Service Enterprise Productivity in Action (SEPIA) model. The research operationalises only one of the five stakeholder groups, the customer interface which incorporates service complexity (SC), customer interactions, customer channel, customer loyalty (CL) (new) as inputs, and CL (referred and repeat) and willingness to pay as output measures.

The research extends our understanding of existing service productivity models with the development of the SEPIA model. Data were collected from 14 organisations operating in the Australian travel and tourism industry, which was analysed using a data envelopment analysis input oriented variable return to scale method as applied to the SEPIA model customer interface.

Four key findings from the research include: customer choice and their ability to pay is a determinant of service productivity; service productivity is a two stage process when measured; SC is not categorical; and quality business systems do impact service productivity.

A limitation of this research is that only one (customer) of the five key stakeholders, customer, employee, manager, supplier and shareholder, was operationalised in this research paper.

The operationalisation of the SEPIA customer interface using transactional data and measuring non-financial, intangible factors of productivity provide managers with insights on what services to offer, when to invest in or promote the use of technology and whether to spend marketing effort on customer acquisition or customer retention.

The SEPIA model positions service firms within a social and service value network and provides a range of customer measures that extend the current capital (K), labour (L), energy (E), materials (M) and service (S), KLEMS measure of productivity and can be used to show the impact customers have on service productivity.

This study aims to identify means to overcome some of the current problems in public service productivity measurement. The objective is to develop a new method for measuring productivity in large public organizations.

The research is carried out as a constructive case study in the City of Helsinki, Finland. Interviews are used in order to identify practical requirements for measurement. The measurement data from around 200 units is used in testing the method.

The new method applies an approach proposed in the literature. It aggregates measurement information from component measures used at the operative level. Based on test calculations and evaluation it is argued that the new method is managerially more relevant than a conventional method.

This study tested the method only to a limited extent. It is necessary to gain more understanding by applying the method in different organizations, and by using longer time periods.

Current productivity measures of public services have been criticized for providing information that lacks managerial relevance. The method described in this study aims to improve relevance in two ways. It enables the gathering of more detailed measurement information from the operative levels of large organizations. In addition, it facilitates the use of different measurement methods in different service providing departments and units.

Many of the existing studies examine productivity measurement at the macro‐level. This study presents a measurement method that is a step forward in developing more sophisticated measurement systems in public organizations. The study also describes and highlights the role of component productivity measurement at the operative level.

“New ways of working” refers to non‐traditional work practices, settings and locations with information and communication technologies (ICT) to supplement or replace traditional ways of working. They are being deployed in knowledge work context in order to increase employees working motivation, job satisfaction and productivity. However, these benefits are not self‐evident. This paper aims to examine the task of measuring the expected benefits.

This paper synthesizes the existing literature on measurement of knowledge work productivity and identifies some key prerequisites and restrictions that should be taken into account when measuring the impacts of organizational change.

The paper proposes a measurement approach for evaluating the impacts of a new ways of working initiative in a knowledge work context.

Previous literature has focused on studying whether facilities and ICT solutions are appropriate from the viewpoint of an individual knowledge worker. However, there is a lack of studies focused on the actual business impacts of different working arrangements.