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Software fault prediction is an important concept that can be applied at an early stage of the software life cycle. Effective prediction of faults may improve the reliability and testability of software systems. As service-oriented architecture (SOA)-based systems become more and more complex, the interaction between participating services increases frequently. The component services may generate enormous reports and fault information. Although considerable research has stressed on developing fault-proneness prediction models in service-oriented systems (SOS) using machine learning (ML) techniques, there has been little work on assessing how effective the source code metrics are for fault prediction. The paper aims to discuss this issue.

In this paper, the authors have proposed a fault prediction framework to investigate fault prediction in SOS using metrics of web services. The effectiveness of the model has been explored by applying six ML techniques, namely, Naïve Bayes, Artificial Networks (ANN), Adaptive Boosting (AdaBoost), decision tree, Random Forests and Support Vector Machine (SVM), along with five feature selection techniques to extract the essential metrics. The authors have explored accuracy, precision, recall, f-measure and receiver operating characteristic curves of the area under curve values as performance measures.

The experimental results show that the proposed system can classify the fault-proneness of web services, whether the service is faulty or non-faulty, as a binary-valued output automatically and effectively.

One possible threat to internal validity in the study is the unknown effects of undiscovered faults. Specifically, the authors have injected possible faults into the classes using Java C3.0 tool and only fixed faults are injected into the classes. However, considering the Java C3.0 community of development, testing and use, the authors can generalize that the undiscovered faults should be few and have less impact on the results presented in this study, and that the results may be limited to the investigated complexity metrics and the used ML techniques.

In the literature, only few studies have been observed to directly concentrate on metrics-based fault-proneness prediction of SOS using ML techniques. However, most of the contributions are regarding the fault prediction of the general systems rather than SOS. A majority of them have considered reliability, changeability, maintainability using a logging/history-based approach and mathematical modeling rather than fault prediction in SOS using metrics. Thus, the authors have extended the above contributions further by applying supervised ML techniques over web services metrics and measured their capability by employing fault injection methods.

The purpose of this paper is to provide insights into the benefits of data‐driven services marketing and provide a conceptual framework for how to link traditional and new sources of customer data and their metrics. Linking data and metrics to strategic and tactical business insights and integrating a variety of metrics into a forward‐looking dashboard to measure marketing ROI and guide future marketing spend is explored.

A detailed synthesis of the literature is conducted and contemporary sources of marketing data are categorized into traditional, digital and neurophysiological. The benefits and drawbacks of each data type are described and advantages of integrating different sources of data are proposed.

The findings point to the importance and untapped potential of data in its ability to inform tactical and strategic marketing decisions. Future challenges, including top management support, ethical considerations and developing data and analytic capabilities, are discussed.

The results demonstrate the need for executive service marketing dashboards that include key metrics that are service‐relevant, complementary and forward‐looking, with proven linkages to business outcomes.

This paper provides a synthesis of data‐driven services marketing and the value of traditional and contemporary metrics. Since the true potential of data‐driven service management in a connected world is still largely unexplored, this paper also delineates fruitful avenues for future research.

Competitive sourcing is the government’s term for transferring the operation of an internal process or function to either an external supplier or a reengineered government team. The competitively sourced function is managed through performance metrics. These metrics must be thorough, appropriate and well designed to ensure the government is receiving the level of service required to fulfill its various missions. This research effort develops a performance metric evaluation system that was synthesized from metric design literature, Total Quality Management concepts, and the Government Performance Results Act. Use of the system in a case study is discussed along with how to evaluate the results. Results indicate that some Air Force performance metrics have insufficient and improperly designed metrics.

For decades academic libraries technical services have adapted to technological advancements and changes in scholarly publishing. Traditional technical services work has decreased as processes were automated (Hertstein, Rabine, & Sweet, 2018). Technical Services departments must proactively identify areas for future growth and metrics for measuring their work. The context and language that these metrics use is vital to their understanding and function. This chapter looks at the usual Technical Services assessment measures and the goals they support. It then considers how these assessments could be reframed in order to support a goal of new service creation in Technical Services. It considers what additional benchmarks could be used as standards and norms to support goals for a future-oriented Technical Services negotiation.

Although the importance of establishing sound metrics is often noted in the logistics literature, few research efforts have examined appropriate metrics for reverse logistics (RL) processes. Through the lens of goal-setting theory, the paper identifies and align salient RL goals and metrics, and uncover some of the most common challenges to RL professionals. The paper aims to discuss these issues.

The paper used open-ended questions to gather qualitative data from 84 RL professionals from the defense industry. A content analysis method was employed to extract and categorize the goals, challenges, and metrics for RL processes.

The paper identifies specific categories of goals, challenges and metrics. Several themes emerged from the study, to include customer service, disposition, costs, and process efficiencies. Using these themes, the paper matched goals to metrics and found a lack of uniformity and noted that metrics and goals often were not matched or were misaligned.

This research is limited by the defense industry sample and the research method. Caution should be used when generalizing the results, and further research is required to empirically test the validity of the findings. Nonetheless, in the context of goal-setting theory, the study contributes to the performance metrics literature by aligning RL metrics with goals and addressing challenges faced by RL practitioners. By investigating the topic from multiple perspectives, the study provides more detailed findings and demonstrates the differences between the inbound and outbound RL processes.

This study provides insight into the metrics used to monitor and control RL processes. The findings may help firms to identify shortcomings and choose metrics that they can employ to align RL processes with firm goals.

The study contributes to the performance metrics literature by aligning RL metrics with goals and addressing challenges faced by RL practitioners. By investigating the topic from both an inbound and outbound perspective, the study provides more detailed findings and demonstrates the differences between the inbound and outbound RL processes.

This paper seeks to measure in a quantitative way the degree of alignment among a set of performance measures between two organizations.

This paper extends Venkatraman's test of coalignment to assess the alignment of a set of performance measures governing a contractual inter‐organizational relationship. The authors applied the test and present coefficients of misalignment across three sets of measures: those used by a service provider involved in the research, those used by customers contracting the services, and those documented in 11 contracts studied.

Results confirmed a high degree of alignment between target and actual operational performance in the contracts. The alignment of customers' financial objectives and contracts' operational metrics was low. Calculations show poor alignment between the objectives of the provider and the contribution received from the contracts.

Some limitations of the conclusions include the small sample of contracts used in the calculations. Further research should include not only actual contracts, but also failed ones.

It is possible that misaligned goals, represented in misaligned performance measures, lead to tensions in intra‐firm relationships. If these tensions are not addressed properly the relationship could be unstable or terminated prematurely. This method of measuring alignment could detect early potential dangers in intra‐firm relationships.

This paper extends Venkatraman's test of coalignment to assess the alignment of a set of performance measures governing a contractual inter‐organizational relationship. Management researchers and business professionals may use this methodology when exploring degrees of alignment of performance measures in intra‐functional and inter‐firm relationships.

The purpose of this paper is to provide a critical discussion of the Leiden Manifesto for libraries already engaged in bibliometric practices. It offers practical recommendations based on the work of the European Association for Research Libraries (LIBER) Working Group on Metrics. This work is in the beginning phase and summarizes literature on the topic, as well as the experiences of the members of the Working Group. The discussion reflects today's growing popularity of (quantitative) research assessment which is seen in enthusiasts introducing new metrics (i.e. altmetrics) and by critics demanding responsible metrics that increase objectivity and equity in evaluations.

This paper is the result of the Working Group on Metrics of the European Association for Research Libraries (LIBER) that critically discussed the practicality of the Leiden Manifesto for libraries.

Full compliance with the Manifesto is time-consuming, expensive and requires a significant increase in bibliometric expertise with respect to both staffing and skill level. Despite these apparent disadvantages, it is recommended that all libraries embrace the Manifesto’s principles. To increase practicality, it is advised that libraries collaborate with researchers, management and other libraries at home and around the world to jointly design and provide services that can be reused within the library community.

Libraries have increasingly been confronted with questions about research assessment, responsible metrics and the role of digital products in evaluations and funding decisions. Although a wide range of recommendations and initiatives are available (e.g. DORA San Francisco Declaration on Research Assessment), many recommendations are not straightforward enough to be implemented from a library perspective. This paper provides assistance for libraries to implement these principles by acknowledging the heterogeneous backgrounds the libraries may stem from.

e‐Supply chains are fast becoming a reality. In order to manage such supply chains efficiently and effectively, traditional measures of supply chain performance are not adequate. The literature search revealed lack of measures and metrics for e‐supply chains. The purpose of this paper is to develop new measures and metrics for monitoring the performance of e‐supply chains.

A framework based on the benefits of e‐supply chains has been used to develop the metrics and measures. The study makes use of focus group discussion by assembling eight experts and practitioners in the field of e‐supply chain to come up with the measures and metrics. A questionnaire is designed with these measures and metrics and is sent to about 300 electronic component manufacturing companies in Malaysia to obtain feedback from the industry practitioners. Appropriate reliability and validity tests are conducted to measure the reliability of the instrument and validity of the constructs.

Through the focus group discussion, this study identifies six metrics and 21 measures. Further validation through the industry practitioners, reveals that these measures are important and some are in use by the industries. The six metrics are: web‐enabled service, data reliability, time and cost, e‐response, invoice presentation and payment and e‐document management metrics.

The study uses a simple framework and a sound methodology to develop new measures and metrics that are relevant for e‐supply chains.

The paper provides a snapshot analysis on the state of service charge management at the point in which its regulatory framework by RICS changed from a voluntary code of practice to a mandatory professional statement.

The data consist of a unique eight-year longitudinal study of service charge statements and practice (2010–2017). Because of the confidential nature of such business-sensitive information, this is a priceless study of real-world practice over such a long period and is able to illustrate both annual compliance and the year-on-year changes. Given this, it is recognised that data are skewed in favour of compliance because they are derived from an actively managed portfolio.

The results continue to illustrate long-running problems of non-compliance with “required” metrics. Given the inherent bias in the data, this is especially difficult to excuse. The paper also analyses the results in the light of the new RICS professional statement, which requires mandatory compliance. Whilst some of the metrics are advisory, there remain questions over how RICS might realistically enforce so many practitioners to change their existing performance and how willing the institution might be to actually prosecute failure. It also revisits the issue of institutionalised benchmarking of standards. Intriguingly, there are islands of almost perfect compliance, which offers an interesting contrast and raises further research questions on why some practitioners provide such exemplary work.

The data are derived from the clients of a UK property management consultancy. This does preclude any randomness to the sampling. However, the richness of the data and the methodology adopted provide valid data.

This work offers both unique data and an eight-year longitudinal analysis, but also a timely comparison with the requirements within a new RICS professional statement. This shift in regulatory regime reinforces the value of the work.