Abstract: Purpose – Given the importance of logistics operations in business-to-consumer (B2C) e-commerce and growing interest in the related environmental effects, the purpose of this paper is to offer an up-to-date literature review on the topic of B2C e-commerce environmental sustainability, specifically from a logistics perspective. Design/methodology/approach – The analysis focussed on a set of 56 papers published from 2001 to 2014 in 38 peer-reviewed international journals. The papers were analyzed and categorized according to the main features of the paper, the research method(s) adopted and the themes tackled. Findings – There is a growing interest in sustainability issues. In the last 14 years, the focus has progressively shifted from the mere identification of the wide-ranging environmental effects of e-commerce to the need for a quantitative evaluation of their impact, although much remains to be done in this regard. Some industries, such as books and grocery, have largely been addressed, however, promising sectors in the e-commerce field, such as clothing and consumer electronics, have only been considered to a certain degree. Moreover, despite the emerging role of multichannel strategies, the environmental implications of the related logistics activities have not yet been studied in detail. Originality/value – B2C e-commerce has grown in popularity, and its environmental implications are currently of key interest. This paper contributes to the understanding of the existing body of knowledge on this topic, presenting an up-to-date classification of articles and highlighting themes for further research activities. From a managerial perspective, this paper helps supply chain managers develop a clear understanding of both the logistics areas with the most impact on environmental sustainability and the KPIs used to quantify the environmental implications of e-commerce logistics operations comprehensively and effectively.

Abstract: In recent years, performance indicators were introduced as a selection mechanism in multi-objective evolutionary algorithms (MOEAs). A very attractive option is the R2 indicator due to its low computational cost and weak-Pareto compatibility. This indicator requires a set of utility functions, which map each objective to a single value. However, not all the utility functions available in the literature scale properly for more than four objectives and the diversity of the approximation sets is sensitive to the choice of the reference points during normalization. In this paper, we present an improved version of a MOEA based on the $R2$ indicator, which takes into account these two key aspects, using the achievement scalarizing function and statistical information about the population's proximity to the true Pareto optimal front. Moreover, we present a comparative study with respect to some other emerging approaches, such as NSGA-III (based on Pareto dominance), Δp-DDE (based on the Δp indicator) and some other MOEAs based on the R2 indicator, using the DTLZ and WFG test problems. Experimental results indicate that our approach outperforms the original algorithm as well as the other MOEAs in the majority of the test instances, making it a suitable alternative for solving many-objective optimization problems.

Abstract: Over the past 20 years, the issue of performance measurement in Social Enterprises (SEs) has gained increasing relevance among researchers and practitioners. From an academic perspective, there has been an explosion in methodologies and tools for assessing social performance and impact, but with little systematic analysis and comparison across different approaches. From a practitioner perspective, SEs need to start measuring their performances in a systemic way, in order to support decision making and ensure accountability towards their stakeholders. In this context, this paper aims to contribute to the state of the art literature by developing an approach that could be applied to/by SEs to measure their results with respect to social, environmental and economic impacts. The proposed approach consists of a “general” PMS model for SEs—i.e., the performance dimensions that should be measured—and a stepwise method to be used by SEs to develop their own PMS. For sake of clarification, the proposed approach is applied to the case of an Italian SE competing in the energy sector to develop a set of key performance indicators.

Abstract: As the supply chains get more complex, the variety of indicators and tools to measure warehouse performance has also increased. Furthermore, the metrics that are used for performance evaluation are assessed in different manners and hence there is not clear definition for some of these metrics. To address these issues, this literature review focuses on operational warehouse performance measurement, for which the warehouse managers need to carry out periodic analysis. Using the content analysis method, performance indicators are acquired from selected papers and are classified according to time, cost, quality and productivity dimensions. The contributions of this literature review are as follows: we present a synthesis of the literature on operational warehouse performance, we provide the definitions for the performance indicators and a framework to demonstrate their boundaries and, finally, based on the literature analysis, we also provide some discussions on current trends in warehouses and propose future...

Abstract: Purpose – The purpose of this paper is to provide a literature review of the performance measurement (PM) in maintenance. The authors aim to discuss the background and development of the PM for maintenance, besides defining the concept of performance measures for maintenance and the frameworks developed. Design/methodology/approach – A detailed and extensive literature search and study was undertaken by the authors on the concept and definition of PM, performance indicators (PIs), maintenance performance indicators and various performance frameworks. The history and theory of PM over different phases of business and technological developments have been critically examined and analysed in this review paper. Findings – This paper reviews and presents the different PIs and PM frameworks like; balanced scorecard (BSC), performance prism, performance pyramid and performance matrix, etc., and identifies their characteristics and shortcomings. After considering related issues and challenges, frameworks and appro...

Abstract: This study examines how the adoption of green supply chain management (GSCM) practices, including green sources, affects environmental and operational performance indicators. A multiple-case study was conducted using large Brazilian firms that have achieved particular success in their sectors and that occupy high positions in important rankings of corporate sustainability. The results of the study indicate that the GSCM practice of “internal environmental management” has the greatest positive effect on environmental performance indicators, and that the GSCM practice of “cooperation with customers” has the greatest positive effect on operational performance indicators. Thus, if a company aims to improve environmental performance (EP), it may create procedures and programs based on the environmental management system and adopt cleaner production initiatives. If a company intends to improve its operational performance (OP), it may respond to audits, improve information exchange between companies and clients and build research and development (R&D) areas to promote environmental innovation.

Abstract: The waste generation rate (WGR) is usually used as a key performance indicator (KPI) to benchmark construction waste management (CWM) performance, with a view to improving the performance continuously. However, existing researches, for different reasons, only investigated a relatively small amount of construction projects, whose WGRs cannot be confidently accepted as KPIs. This study develops a set of more reliable KPIs/WGRs using an available big dataset on CWM in Hong Kong. By mining the 2,212,026 waste disposal records generated from 5764 projects in two consecutive years of 2011 and 2012, the WGRs/KPIs are revisited and refined. Demolition is found the most wasteful works. New building, and maintenance and renovation (M&R) works individually produce the least waste amount but by accumulating all M&R works, their contribution to the total amount of construction waste could be phenomenal. Based on the more reliable WGRs from the big data, CWM performance benchmarks for different categories of projects are set up. A contractor can benchmark its CWM performance against its counterparts or its past performance as ‘Good’, ‘Average’, and ‘Not-so-good’, and thus identify better CWM practices that induce superior performance. Based on the benchmarks, the government may consider setting up a WGR-step toll system to encourage those ‘Not-so-good’ contractors to perform well in the future, and initiate incentives to the companies conducting ‘Good’ projects to spur better CWM performance. Overall, the WGRs derived from the big data and more robust analyses provide a very powerful and handy tool for CWM.

Abstract: There has been a growing use of performance-based research funding systems (PRFS) as a policy tool. With the introduction of the Publication Indicator in 2004, Norway joined this international trend in which the allocation of basic funds is increasingly linked to performance indicators. The purpose of this article is to present and discuss the main results of a recent evaluation of the Norwegian Publication Indicator, which examines the Indicator’s impact on publishing patterns, its properties, and how it has functioned in practice. This includes both a broad range of potential effects such as the Indicator’s impact on the quantity and the quality of publications, Norwegian language publishing, and length of articles and monographs. It also includes an examination of properties such as the Indicator’s legitimacy and transparency, how it functions as a measure of research performance across different fields, its use as a management tool, and how the system is organized and administrated in practice. In examining these questions, the article draws on a number of different data sources, including large-scale surveys of both researchers and research managers, multilevel case studies, and bibliometric analysis. The article concludes with a discussion of the implications of the analysis both for further development of the Norwegian Model and for PRFS in general.

Abstract: Purpose – A growing body of literature has begun in the direction of supply chain performance measurement. However, selecting the appropriate set of key performance indicators (KPIs) for measuring supply chain performance have always remained a challenge. The purpose of this paper is to identify the KPIs and categorize them specifically for measuring retail supply chain performance. Design/methodology/approach – A qualitative approach, based on literature has been adopted. Published literature from refereed journals on supply chain performance measurement has been considered and various approaches for developing KPIs have been studied to develop a theoretical framework for performance measurement in retail supply chain. Findings – The paper identifies key indicators for performance measurement and classifies them into four major categories: transport optimization, information technology optimization, inventory optimization and resource optimization. These key indicators are arranged precisely for retail i...

Abstract: Introduction to Benchmarking.- Performance Measures.- Performance Models.- Performance Analysis - DEA.- Performance Analysis - SFA.- Performance Planning.- Performance Restructuring.- Performance Contracting.- Interactive Benchmarking.

Abstract: Simulation provides a flexible approach to analyzing business processes. Through simulation experiments various “what if” questions can be answered and redesign alternatives can be compared with respect to key performance indicators. This chapter introduces simulation as an analysis tool for business process management. After describing the characteristics of business simulation models, the phases of a simulation project, the generation of random variables, and the analysis of simulation results, we discuss 15 risks, i.e., potential pitfalls jeopardizing the correctness and value of business process simulation. For example, the behavior of resources is often modeled in a rather naive manner resulting in unreliable simulation models. Whereas traditional simulation approaches rely on hand-made models, we advocate the use of process mining techniques for creating more reliable simulation models based on real event data. Moreover, simulation can be turned into a powerful tool for operational decision making by using real-time process data.

Abstract: Background: Static nature of performance reporting systems in health care sector has resulted in inconsistent, incomparable, time consuming, and static performance reports that are not able to transparently reflect a round picture of performance and effectively support healthcare managers’ decision makings. So, the healthcare sector needs interactive performance management tools such as performance dashboards to measure, monitor, and manage performance more effectively. The aim of this article was to identify key issues that need to be addressed for developing high-quality performance dashboards in healthcare sector. Methods: A literature review was established to search electronic research databases, e-journals collections, and printed journals, books, dissertations, and theses for relevant articles. The search strategy interchangeably used the terms of “dashboard”, “performance measurement system” and “executive information system” with the term of “design” combined with operator “AND”. Search results (n=250) were adjusted for duplications, screened based on their abstract relevancy and full-text availability (n=147) and then assessed for eligibility (n=40). Eligible articles were included if they had explicitly focused on dashboards, performance measurement systems or executive information systems design. Finally, 28 relevant articles included in the study. Results: Creating high-quality performance dashboards requires addressing both performance measurement and executive information systems design issues. Covering these two fields, identified contents were categorized to four main domains: KPIs development, Data Sources and data generation, Integration of dashboards to source systems, and Information presentation issues. Conclusion: This study implies the main steps to develop dashboards for the purpose of performance management. Performance dashboards developed on performance measurement and executive information systems principles and supported by proper back-end infrastructure will result in creation of dynamic reports that help healthcare managers to consistently measure the performance, continuously detect outliers, deeply analyze causes of poor performance, and effectively plan for the future.

Abstract: Sustainable industrial development can be advanced through the development and application of sustainability metrics. This study addressed the application of social sustainability metrics to the measurement of sustainability performance within process industry and to metal production at the plant level in particular. The applied social sustainability indicators are one part of the overall sustainability index which aims at presenting a balanced and holistic view of plant-level sustainability performance. Application of plant-level indicators can support informed decision-making and fill in potential gaps in corporate-level assessments and reporting initiatives with respect to plant-level social sustainability performance. The social part of the overall index provides information on both in-plant sustainability performance and on the direct and in-direct impacts of plant operations on the surrounding society with special emphasis on the supply chain and emerging social due diligence aspects. The results of...

Abstract: Sports analytics in general, and football (soccer in USA) analytics in particular, have evolved in recent years in an amazing way, thanks to automated or semi-automated sensing technologies that provide high-fidelity data streams extracted from every game. In this paper we propose a data-driven approach and show that there is a large potential to boost the understanding of football team performance. From observational data of football games we extract a set of pass-based performance indicators and summarize them in the H indicator. We observe a strong correlation among the proposed indicator and the success of a team, and therefore perform a simulation on the four major European championships (78 teams, almost 1500 games). The outcome of each game in the championship was replaced by a synthetic outcome (win, loss or draw) based on the performance indicators computed for each team. We found that the final rankings in the simulated championships are very close to the actual rankings in the real championships, and show that teams with high ranking error show extreme values of a defense/attack efficiency measure, the Pezzali score. Our results are surprising given the simplicity of the proposed indicators, suggesting that a complex systems' view on football data has the potential of revealing hidden patterns and behavior of superior quality.

Abstract: Food chain logistics plays an important role in the sustainability performance of the food sector. Therefore, project SCALE (Step Change in Agri-food Logistics Ecosystems) started as a collaborative international project, aiming for tools and frameworks for the food sector to make a step change in operational practices. A sustainability framework is introduced to propose a structured and rational method for assessing sustainability. Next, we empirically apply the framework, based upon explorative web-based research and semi-structured interviews with the best practice players in the field in the Netherlands, the UK and France. Findings provide clear insights into the current state of the art regarding the use of sustainability performance indicators, companies’ sustainability strategies, supply chain redesign strategies currently applied in practice and experienced barriers to sustainability improvement. Overall, logistics service providers seem to have a wait-and-see attitude towards sustainability where...

Abstract: This study aims to analyze lean manufacturing effect on financial, non-financial and sustainability performances.Causal maps are used for defining the inter-relation and intra-relation of lean factors.Bayesian Belief Networks are used for linking the lean factors.Effects of various combinations of lean factors on business performance are analyzed.Developed scenarios can be a lead for defining the business strategies based on lean thinking in any industry. The challenge of agility for adopting new business norms creates the need for measuring performance under changing conditions. This study aims to demonstrate the financial and non-financial consequences of implementing different combinations of lean techniques on the business performance. Bayesian Belief Network is used in studying the effects of factors under changing conditions. There are seven lean factors and four achievements studied to analyze the impact on three performance indicators. Bayesian Belief Network is constructed on the lean aspects that stimuli flexibility, reliability, quality and time of operations, which will have positive impacts on the financial, non-financial and sustainability performances of suppliers. A case study is carried out for suppliers in the automotive industry and scenarios with different combinations of lean factors are studied. This study gives a new vision in applying Bayesian network for business performance measures considering both the tangible and intangible results under changing business conditions.

Abstract: The development of advanced techniques for process monitoring and fault diagnosis using both model-based and data-driven approaches has led to many practical applications. One issue that has not been considered in such applications is the ability to deal with key performance indicators (KPIs) that are only sporadically measured and with significant time delay. Therefore, in this paper, the data-driven design of diagnostic-observer-based process monitoring schemes is extended to include the ability to detect changes given infrequently measured KPIs. The extended diagnostic observer is shown to be stable and hence able to converge to the true value. The proposed method is tested using both Monte Carlo simulations and the Tennessee-Eastman problem. It is shown that although time delay and sampling time increase the detection delay, the overall effect can be mitigated by using a soft sensor. Furthermore, it is shown that the results are not strongly dependent on the sampling time, but do depend on the time delay. Therefore, the proposed soft-sensor-based monitoring scheme can efficiently detect faults even in the absence of direct process information.

Abstract: Based on a systematic investigation on the experimental, theoretical and numerical results on various tubes under axial compression/impact including our own tests, a set of key performance indicators (KPIs) for assessing and comparing the energy absorbing performance of tubular structures with various configurations is proposed, so as to guide the design of energy absorbers whilst to facilitate parameter optimization. The five KPIs proposed on the basis of mechanical analyses are effective stroke ratio (ESR), nondimensional load-carrying capacity (NLC), specific energy absorption (SEA), effectiveness of energy absorption (EEA) and undulation of load-carrying capacity (ULC). Moreover, by considering the influence of foam filling, these five KPIs are also modified and extended to the foam-filled tubes. The paper presents a series of diagrams to compare the energy absorbing performance of various tubes in terms of the five KPIs as described above. It transpires that the energy absorption performance of circular tubes is superior to that of square tubes. It is also confirmed that the mass of foam fillers results in reductions of SEA and EEA, though foam fillers will greatly improve the NLC of empty tubes. The novelty of the present study is displayed on the following aspects: (1) uniquely defining the effective stroke by the maximum point of "energy efficiency" f so as to avoid ambiguity which appeared in the literature; (2) instead of a single indicator such as SEA, proposing a set of five KPIs to comprehensively assess the performance of energy absorbers and (3) validating the usefulness of the proposed KPIs by comparing the performance of various tubular structures used as energy absorbers.

Abstract: Objectives This study was to evaluate the performance of the newly developed information system (IS) implemented on July 1, 2014 at three public hospitals in Korea. Methods User satisfaction scores of twelve key performance indicators of six IS success factors based on the DeLone and McLean IS Success Model were utilized to evaluate IS performance before and after the newly developed system was introduced. Results All scores increased after system introduction except for the completeness of medical records and impact on the clinical environment. The relationships among six IS factors were also analyzed to identify the important factors influencing three IS success factors (Intention to Use, User Satisfaction, and Net Benefits). All relationships were significant except for the relationships among Service Quality, Intention to Use, and Net Benefits. Conclusions The results suggest that hospitals should not only focus on systems and information quality; rather, they should also continuously improve service quality to improve user satisfaction and eventually reach full the potential of IS performance.