Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Climate change performance measurement, control and accountability in English local areas

Purpose – This paper aims to consider how climate change performance is measured and accounted for within the performance framework for local authority areas in England adopted in 2008. It critically evaluates the design of two mitigation and one adaptation indicators that are most relevant to climate change. Further, the potential for these performance indicators to contribute to climate change mitigation and adaptation is discussed. Design/methodology/approach – The authors begin by examining the importance of the performance framework and the related Local Area Agreements (LAAs), which were negotiated for all local areas in England between central government and Local Strategic Partnerships (LSPs). This development is located within the broader literature relating to new public management. The potential for this framework to assist in delivering the UK's climate change policy objectives is researched in a two-stage process. First, government publications and all 150 LAAs were analysed to identify the level of priority given to the climate change indicators. Second, interviews were conducted in spring 2009 with civil servants and local authority officials from the English West Midlands who were engaged in negotiating the climate change content of the LAAs. Findings – Nationally, the authors find that 97 per cent of LAAs included at least one climate change indicator as a priority. The indicators themselves, however, are perceived to be problematic – in terms of appropriateness, accuracy and timeliness. In addition, concerns were identified about the level of local control over the drivers of climate change performance and, therefore, a question is raised as to how LSPs can be held accountable for this. On a more positive note, for those concerned about climate change, the authors do find evidence that the inclusion of these indicators within the performance framework has helped to move climate change up the agenda for local authorities and their partners. However, actions by the UK's new coalition government to abolish the national performance framework and substantially reduce public expenditure potentially threaten this advance. Originality/value – This paper offers an insight into a new development for measuring climate change performance at a local level, which is relatively under-researched. It also contributes to knowledge of accountability within a local government setting and provides a reference point for further research into the potential role of local actions to address the issue of climate change.

Semantic representation for comparison of performance measurement indicators

Indicators are widely used by organizations as a way of evaluating, measuring and classifying organizational performance. As part of performance evaluation systems, indicators are often shared or compared across internal sectors or with other organizations. However, indicators can be vague and imprecise, and also can lack semantics, making comparisons with other indicators difficult. Thus, this paper presents a knowledge model based on an ontology that may be used to represent indicators semantically and generically, dealing with the imprecision and vagueness, and thus facilitating better comparison. Semantic technologies are shown to be suitable for this solution, so that it could be able to represent complex data involved in indicators comparison.

Ontology for performance measurement indicators’ comparison

Indicators are widely used by organizations as a way of evaluating, measuring and classifying organizational performance. As part of performance evaluation systems, indicators are often shared or compared across internal sectors or with other organizations. However, indicators can be vague and imprecise, and also can lack semantics, making comparisons with other indicators difficult. Thus, this paper presents a knowledge model based on an ontology that may be used to represent indicators semantically and generically, dealing with the imprecision and vagueness, and thus facilitating better comparison. Semantic technologies are shown to be suitable for this solution, so that it could be able to represent complex data involved in indicators comparison.

Performance measurement with multiple interrelated variables and threshold target levels:evidence from retail firms in the US

In this study, we developed a DEA-based performance measurement methodology that is consistent with performance assessment frameworks such as the Balanced Scorecard. The methodology developed in this paper takes into account the direct or inverse relationships that may exist among the dimensions of performance to construct appropriate production frontiers. The production frontiers we obtained are deemed appropriate as they consist solely of firms with desirable levels for all dimensions of performance. These levels should be at least equal to the critical values set by decision makers. The properties and advantages of our methodology against competing methodologies are presented through an application to a real-world case study from retail firms operating in the US. A comparative analysis between the new methodology and existing methodologies explains the failure of the existing approaches to define appropriate production frontiers when directly or inversely related dimensions of performance are present and to express the interrelationships between the dimensions of performance.

What counts versus what can be counted:the complex interplay of market orientation and marketing performance measurement

Market orientation (MO) and marketing performance measurement (MPM) are two of the most widespread strategic marketing concepts among practitioners. However, some have questioned the benefits of extensive investments in MO and MPM. More importantly, little is known about which combinations of MO and MPM are optimal in ensuring high business performance. To address this research gap, the authors analyze a unique data set of 628 firms with a novel method of configurational analysis: fuzzy-set qualitative comparative analysis. In line with prior research, the authors find that MO is an important determinant of business performance. However, to reap its benefits, managers need to complement it with appropriate MPM, the level and focus of which vary across firms. For example, whereas large firms and market leaders generally benefit from comprehensive MPM, small firms may benefit from measuring marketing performance only selectively or by focusing on particular dimensions of marketing performance. The study also finds that many of the highest-performing firms do not follow any of the particular best practices identified.

Comparative performance between two photogrammetric systems and a reference laser tracker network for large-volume industrial measurement

This paper determines the capability of two photogrammetric systems in terms of their measurement uncertainty in an industrial context. The first system – V-STARS inca3 from Geodetic Systems Inc. – is a commercially available measurement solution. The second system comprises an off-the-shelf Nikon D700 digital camera fitted with a 28 mm Nikkor lens and the research-based Vision Measurement Software (VMS). The uncertainty estimate of these two systems is determined with reference to a calibrated constellation of points determined by a Leica AT401 laser tracker. The calibrated points have an average associated standard uncertainty of 12·4 μm, spanning a maximum distance of approximately 14·5 m. Subsequently, the two systems’ uncertainty was determined. V-STARS inca3 had an estimated standard uncertainty of 43·1 μm, thus outperforming its manufacturer's specification; the D700/VMS combination achieved a standard uncertainty of 187 μm.

Measuring and managing performance in extended enterprises

Purpose - The purpose of this research paper is to demonstrate how existing performance measurement may be adopted to measure and manage performance in extended enterprises. Design/methodology/approach - The paper reviews the literature in performance measurement and extended enterprises. It explains the collaborative architecture of an extended enterprise and demonstrates this architecture through a case study. A model for measuring and managing performance in extended enterprises is developed using the case study. Findings - The research found that due to structural differences between traditional and extended enterprises, the systems required to measure and manage the performance of extended enterprises, whilst being based upon existing performance measurement frameworks, would be structurally and operationally different. Based on this, a model for measuring and managing performance in extended enterprises is proposed which includes intrinsic and extrinsic inter-enterprise coordinating measures. Research limitations/implications - There are two limitations this research. First, the evidence is based on a single case, thus further cases should be studied to establish the generalisibility of the presented results. Second, the practical limitations of the EE performance measurement model should be established through longitudinal action research. Practical implications - In practice the model proposed requires collaborating organisations to be more open and share critical performance information with one another. This will require change in practices and attitudes. Originality/value - The main contribution this paper makes is that it highlights the structural differences between traditional and collaborative enterprises and specifies performance measurement and management requirements of these collaborative organisations. © Emerald Group Publishing Limited.

Emergent strategy and the measurement of performance:the formulation of performance indicators at the microlevel

This article presents some evidence on an aspect of the design of a strategic control system, at the microlevel, within a single organization. The research we report used an ethnographic approach to provide an understanding of strategy formulation. Our aim is to contribute to an area of literature which is of increasing significance, but relatively underdeveloped in terms of the application of in-depth, field-research techniques. We take an intensive look at the manner in which performance measures are formulated, at the microlevel, within a single organization. The article presents, as an in-depth case analysis, the experience of a fisheries holding company in New Zealand. The article recounts the experiences of managers within the organization of the process of identification of such things as critical success factors and key performance indicators (KPIs) and, more broadly, the formulation of a strategic performance measurement system.