Efficient computation of key performance indicators in a distance learning university

2019 ◽  
Vol 47 (2) ◽  
pp. 96-105 ◽  
Author(s):  
Riccardo Pecori ◽  
Vincenzo Suraci ◽  
Pietro Ducange
Keyword(s):  
Big Data ◽  
Distance Learning ◽  
Performance Indicators ◽  
Key Performance Indicators ◽  
Data Representation ◽  
Efficient Computation ◽  
Educational Decisions ◽  
Content Type ◽  
Educational Sources ◽  
And Performance

Purpose Managing efficiently educational Big Data, produced by Virtual Learning Environments, is becoming a compelling necessity, especially for those universities providing distance learning. This paper aims to propose a possible framework to compute efficiently key performance indicators, summarizing the trends of students’ academic careers, by using educational Big Data. Design/methodology/approach The framework is designed and implemented in a distributed fashion. The parallel computation of the indicators through Map and Reduce nodes is carefully described, together with the workflow of data, from the educational sources to a NoSQL database and to the learning analytics engine. Findings This framework was tested at eCampus University, an Italian distance learning institution, and it was able to significantly reduce the amount of time needed to compute key performance indicators. Moreover, by implementing a proper data representation dashboard, it resulted in a useful help and support for educational decisions and performance analyses and for revealing possible criticalities. Originality/value The framework proposed integrates for the first time, to the best of the authors’ knowledge, a set of modules, designed and implemented in a distributed fashion, to compute key performance indicators for distance learning institutions. It can be used to analyze the dropouts and the outcomes of students and, therefore, to evaluate the performances of universities, which can, in turn, propose effective improvements toward enhancing the overall e-learning scenario.

European academic libraries Key Performance Indicators (KPI)

2019 ◽  
Vol 20 (3) ◽  
pp. 143-158
Author(s):  
Cecile Swiatek
Keyword(s):  
Comparative Study ◽  
Academic Libraries ◽  
Performance Indicators ◽  
Research Performance ◽  
Key Performance Indicators ◽  
Strong Increase ◽  
Library Services ◽  
Content Type ◽  
And Performance ◽  
Teaching Learning

Purpose The French academic libraries directors association (ADBU) launched and updated a European comparative study on Key Performance Indicators (KPI) in Academic Libraries over the 2013–2017 period. The purpose of this paper is to briefly present the ADBU initiative; its main focus is how to use these figures to ground decision making process, notably so as to better assess the contribution of libraries in student success or research performance. Design/methodology/approach As universities and academic libraries are facing research evolutions and teaching/learning new models, a strong increase in students’ number is observed everywhere in Europe. This trend will most probably continue in the coming years and the pressure on academic libraries will grow. That is why the French ADBU took the initiative to launch a European comparative study on key and performance indicators in Academic Libraries over the 2013–2016 period. Data were updated in 2019, covering 2017 figures and including additional countries. Findings Thanks to the European partners and the help of a consultant firm, the first observations were updated with the 2017 figures and the country scope grew broader. Libraries buildings and equipment, space and seats per student, opening days and hours, frequentation rate, library services, users training, staff per student/documentary budgets/total expenditure, staff training, documentation loans/consultation/downloads: these KPI are gathered and can be compared in both relative and absolute value. Originality/value The ADBU initiative is unique, results are widely shared.

Development of an integrated performance measurement framework for lean organizations

2018 ◽  
Vol 29 (1) ◽  
pp. 41-84 ◽  
Author(s):  
Narpat Ram Sangwa ◽  
Kuldip Singh Sangwan
Keyword(s):  
Performance Measurement ◽  
Performance Indicators ◽  
Manufacturing Process ◽  
Key Performance Indicators ◽  
Supplier Management ◽  
The Body ◽  
Customer Management ◽  
Content Type ◽  
Measurement Framework ◽  
Integrated Performance

Purpose The purpose of this paper is to propose an integrated performance measurement framework to measure the effect of lean implementation throughout all functions of an organization. Design/methodology/approach The paper identifies the seven categories representing all organizational functions. These categories have been divided into 26 performance dimensions and key performance indicators (KPIs) for each performance dimension have been identified to measure lean performance. The interrelationship of each category with lean principles and/or lean wastes has been identified. KPIs are developed on the basis of identified criteria, frequency analysis of existing literature, and discussion with industry professionals. Finally, an integrated performance measurement framework is proposed. Findings The proposed framework evaluates the organization under seven categories – manufacturing process, new product development (NPD), human resource management, finance, administration, customer management, and supplier management. In total, 26 dimensions and 119 key performance indicators have been identified under the seven categories. Research limitations/implications The proposed framework is a conceptual framework and it is to be tested by empirical and cross-sectional studies. Originality/value The main novelty of the research is that the leanness of the organization has been measured throughout the supply chain of the organization in an integrated way. The various areas of measurement are manufacturing process, NPD, finance, administration, customer management, and supplier management. Further, the proposed KPIs are also categorized as qualitative or quantitative, strategic or operational, social or technical, financial or non-financial, leading or lagging, static or dynamic. This paper contributes to the body of knowledge in performance measurement.

Airline effective operations strategy during COVID-19 pandemic: across regional worldwide survey

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yazan Khalid Abed-Allah Migdadi
Keyword(s):  
Performance Indicators ◽  
Secondary Data ◽  
Operations Strategy ◽  
Quantitative Methodology ◽  
Resilience Theory ◽  
Operational Strategies ◽  
Content Type ◽  
And Performance ◽  
International Airlines ◽  
Bounce Back

Purpose This study aims to identify the effective operational strategies for airlines in a pandemic that allow them to recover and bounce back smoothly. Design/methodology/approach This study adopted quantitative methodology based on secondary data published by the airlines related to operational and performance indicators. The total number of airlines surveyed was 145. The sample of study covers all the following regions: Africa, Asia, Europe, the Middle East, North America and South America. The data analysis of this research passed through several phases to compare the situation before and during pandemic period. Findings The effective operational strategy patterns during the outbreak of the COVID-19 pandemic comprise three hybrid strategies and one scheduling strategy. It appears from these strategy models that four strategic alternatives are available for international airlines to adopt, while two strategic alternatives are available for regional airlines. The strategy alternatives for regional and international airlines are all effective, but those of the international airlines are the more effective ones. Originality/value Previous studies rarely adopted the theory of operations strategy configuration (emphasizing taxonomies-based perspective) and the organizational resilience theory (emphasizing capability-based perspective) to identify the effective airlines operations strategy patterns in a pandemic, that allow airlines to recover and bounce back smoothly by analyzing the practices of airlines from different geographic regions worldwide.

Key performance indicators for a sustainable recovery strategy in health-care supply chains: COVID-19 pandemic perspective

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Towfique Rahman ◽  
Md. Abdul Moktadir ◽  
Sanjoy Kumar Paul
Keyword(s):  
Health Care ◽  
Supply Chains ◽  
Performance Indicators ◽  
Large Scale ◽  
Production Capacity ◽  
Key Performance Indicators ◽  
Recovery Strategy ◽  
Content Type ◽  
Global Pandemic ◽  
Sustainable Recovery

Purpose Supply chains’ (SCs’) sustainability practices and recovery strategies are attaining popularity in academia and industries to improve the resilience of the SCs and to manage large-scale disruptions. The global pandemic caused by the COVID-19 has raised the question of the sustainability of essential health-care products’ SCs of Bangladesh. It is an essential avenue for making the life of people safe and secure. Despite its importance, most of the health-care SCs in Bangladesh are struggling to meet the demand of its nation due to capacity shortage, technological backwardness of the manufacturers, delivery capacity shortages and less advanced forecasting capabilities. Therefore, this study aims to investigate the key performance indicators (KPIs) of a sustainable recovery strategy in the context of health-care SCs considering the COVID-19 pandemic. Design/methodology/approach This study used a dynamic method named graph theory and matrix approach to evaluate the most critical KPIs of a sustainable recovery strategy in the context of Bangladeshi health-care SCs. Findings The result revealed that dynamic forecasting and planning with a smooth delivery and distribution support system, production capacity diversification and having alternative or multiple suppliers during extraordinary disruptions may aid in the sustainability of the health-care SCs in Bangladesh. Originality/value This study is unique as no previous study has identified and examined the sustainable recovery strategy perspective KPIs considering the COVID-19 pandemic in the context of Bangladeshi health-care SCs. This study will also add value by guiding decision-makers of the health-care SCs of Bangladesh to adopt strategies toward the sustainability of SCs.

Value that matters: intellectual capital and big data to assess performance in healthcare. An empirical analysis on the European context

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ginevra Gravili ◽  
Francesco Manta ◽  
Concetta Lucia Cristofaro ◽  
Rocco Reina ◽  
Pierluigi Toma
Keyword(s):  
Big Data ◽  
Organizational Performance ◽  
Healthcare System ◽  
Healthcare Sector ◽  
Healthcare Organizations ◽  
Content Type ◽  
Structural Capital ◽  
And Performance ◽  
The Relationship

PurposeThe aim of this paper is to analyze and measure the effects of intellectual capital (IC), i.e. human capital (HC), relational capital (RC) and structural capital (SC), on healthcare industry organizational performance and understanding the role of data analytics and big data (BD) in healthcare value creation (Wang et al., 2018). Through the assessment of determined variables specific for each component of IC, the paper identifies the guidelines and suggests propositions for a more efficient response in terms of services provided to citizens and, specifically, patients, as well as predicting effective strategies to improve the care management efficiency in terms of cost reduction.Design/methodology/approachThe study has a twofold approach: in the first part, the authors operated a systematic review of the academic literature aiming to enquire the relationship between IC, big data analytics (BDA) and healthcare system, which were also the descriptors employed. In the second part, the authors built an econometric model analyzed through panel data analysis, studying the relationship between IC, namely human, relational and structural capital indicators, and the performance of healthcare system in terms of performance. The study has been conducted on a sample of 28 European countries, notwithstanding the belonging to specific international or supranational bodies, between 2011 and 2016.FindingsThe paper proposes a data-driven model that presents new approach to IC assessment, extendable to other economic sectors beyond healthcare. It shows the existence of a positive impact (turning into a mathematical inverse relationship) of the human, relational and structural capital on the performance indicator, while the physical assets (i.e. the available beds in hospitals on total population) positively mediates the relationship, turning into a negative impact of non-IC related inputs on healthcare performance. The result is relevant in terms of managerial implications, enhancing the opportunity to highlight the crucial role of IC in the healthcare sector.Research limitations/implicationsThe relationship between IC indicators and performance could be employed in other sectors, disseminating new approaches in academic research. Through the establishment of a relationship between IC factors and performance, the authors implemented an approach in which healthcare organizations are active participants in their economic and social value creation. This challenges the views of knowledge sharing deeply held inside organizations by creating “new value” developed through a more collaborative and permeated approach in terms of knowledge spillovers. A limitation is given by a fragmented policymaking process which carries out different results in each country.Practical implicationsThe analysis provides interesting implications on multiple perspectives. The novelty of the study provides interesting implications for managers, practitioners and governmental bodies. A more efficient healthcare system could provide better results in terms of cost minimization and reduction of hospitalization period. Moreover, dissemination of new scientific knowledge and drivers of specialization enhances best practices sharing in the healthcare sector. On the other hand, an improvement in preventive medicine practices could help in reducing the overload of demand for curative treatments, on the perspective of sharply decreasing the avoidable deaths rate and improving societal standards.Originality/valueThe authors provide a new holistic framework on the relationship between IC, BDA and organizational performance in healthcare organizations through a systematic review approach and an empirical panel analysis at a multinational level, which is quite a novelty regarding the healthcare. There is little research focussed on healthcare industries' organizational performance, and, specifically, most of the research on IC in healthcare delivered results in terms of theoretical contribution and qualitative analyzes. The authors even contributed to analyze the healthcare industry in the light of the possible existence of synergies and networks among countries.

TQM practices and its performance effects – an integrated model

2019 ◽  
Vol 36 (8) ◽  
pp. 1318-1344 ◽  
Author(s):  
Anu P. Anil ◽  
Satish K.P.
Keyword(s):  
Customer Satisfaction ◽  
Performance Indicators ◽  
Indirect Effects ◽  
Integrated Model ◽  
Mediating Effect ◽  
Common Method ◽  
Direct And Indirect Effects ◽  
Content Type ◽  
Performance Effects ◽  
And Performance

Purpose Total quality management practices have been embraced by many quality-oriented firms around the world in order to improve performance in terms of quality, productivity, customer satisfaction and profitability. The purpose of this paper is to investigate the direct and indirect effects of TQM practices on various performance indicators specifically in the Indian manufacturing context. This paper focuses on developing an integrated model encompassing significant structural relations showing the linkage between TQM practices and multiple performance indicators – quality performance, customer satisfaction level, operating performance, employee performance, innovation performance, society results and financial performance. Apart from analyzing the direct relationship between constructs, the main purpose of this work is also to identify all the possible mediation effects of performance indicators on others using structural equation modeling (SEM). Design/methodology/approach An in-depth literature review was conducted to identify the key practices for the successful implementation of TQM in an organization as well as to explore TQM-performance effects. As a result, four TQM practices and seven performance indicators were identified. The data were collected from 260 Indian manufacturing organizations. After confirming the reliability and validity using exploratory and confirmatory factor analysis, the proposed hypotheses were tested using SEM. Findings Through testing the proposed hypothesized structural model, the direct and indirect effects of TQM practices have been examined. Moreover, this work developed an integrated model showing the interrelationships between TQM practices and performance indicators identified. The findings gave an insight that the effective implementation of TQM practices assists in reaping benefits in the every facet of an organization. By implementing these practices effectively, managers can expect to realize improvement in all these performance areas. Research limitations/implications This study is subject to certain limitations. Even if all variables were found to be reliable, valid and satisfactory non-response bias test results, the remote possibility of bias in the data might not be fully ruled out. There is a probability of occurrence of common method variance and common method bias, since the data for both dependent and independent variables were collected from the same respondents in the organization. Additionally data on performance indicators were based on the respondent’s assessment and awareness only. The mediating relationship between individual TQM practice and performance indicators can be investigated in future studies. Since society results are a necessity in future, the direct and indirect practices focusing toward this can be explored. In addition, there is a research scope to identify the moderating effect of contextual factors such as degree of TQM implementation, scope of operation and type of organization. Practical implications The findings of the research offer some potentially valuable insights into the relevance of TQM practices and its strong linkage on various performance indicators, through which the overall organization performance can be enhanced. By implementing these practices effectively, managers can expect to realize improvement in all these performance areas. Hence, the managers can adopt this approach to assess their organization’s level in the quality path and as a guideline in implementing TQM practices. They can also measure the impacts of TQM practices on multiple performance measures in order to evaluate their TQM initiatives. Especially the deployment of quality culture is a requisite to excel in the every facet of performance. The positive relationship between TQM practices and various performance indicators can motivate the managers to allocate resources in time, effort and capital for TQM implementation in pursuing quality, leading to customer retention and competitiveness. The findings of the study strongly suggest the need for the holistic implementation of TQM practices for the survival of the organization. Originality/value While there is a considerable volume of researches carried out to investigate the linkage between TQM and organization’s performance across the globe, still little is evidenced regarding the mediating effect of performance indicators on others, especially in the Indian manufacturing context. The present paper attempts to extend and add knowledge to this line of research and to bridge the gap and provide sufficient empirical evidence specifically in the Indian scenario. Thereby helps the organization to follow a guideline to improve the overall performance.

Developing key performance indicators for hospital facilities management services: a developing country perspective

2020 ◽  
Vol 27 (9) ◽  
pp. 2715-2735 ◽  
Author(s):  
Daniel Amos ◽  
Cheong Peng Au-Yong ◽  
Zairul Nisham Musa
Keyword(s):  
Performance Measurement ◽  
Balanced Scorecard ◽  
Performance Indicators ◽  
Principal Component ◽  
Key Performance Indicators ◽  
Public Hospitals ◽  
Facilities Management ◽  
Content Type ◽  
Significant Difference ◽  
Level Of Importance

PurposeKey performance indicators (KPIs) help to monitor performance, thereby revealing the gap between planned and executed results relative to organizational objectives. The purpose of this paper is to develop KPIs for performance measurement of facilities management (FM) services in public hospitals.Design/methodology/approachFollowing a comprehensive literature review of KPIs in FM, a set of KPIs were first selected. This was then subjected to content validation by experts. Thereafter a questionnaire survey was conducted to identify participants perception on the level of importance of the proposed KPIs. The main analytical tool used was SPSS factor analysis/principal component extraction.FindingsAdapting an expanded balanced scorecard typology, the paper identifies 17 KPIs, which are useful for performance improvement of FM. The study also introduces new financial dimensions beyond the traditional cost and profit-centered metrics.Research limitations/implicationsThe study was limited to three FM services. Although the results of the Kruskal–Wallis test shows no significant difference in the level of importance on more than 80% of the indicators, larger sample is required in future studies to examine indicator preference for the respective services. An empirical study to test the proposed indicators to measure FM performance could also be a next step.Originality/valueThe paper presents the first step to develop performance indicators, which are of relevance to FM performance measurement and could be utilized to improve performance. The indicators are largely generic and can easily be adapted by other FM service sectors for performance measurement.

Big data and performance measurement research: trends, evolution and future opportunities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Alberto Sardi ◽  
Enrico Sorano ◽  
Valter Cantino ◽  
Patrizia Garengo
Keyword(s):  
Big Data ◽  
Performance Measurement ◽  
Performance Measurement System ◽  
Future Research ◽  
Holistic View ◽  
Content Type ◽  
Digital Revolution ◽  
Research Opportunities ◽  
And Performance ◽  
Number Of Publications

Purpose Current literature recognised big data as a digital revolution affecting all organisational processes. To obtain a competitive advantage from the use of big data, an efficient integration in a performance measurement system (PMS) is needed, but it is still a “great challenge” in performance measurement research. This paper aims to review the big data and performance measurement studies to identify the publications’ trends and future research opportunities. Design/methodology/approach The authors reviewed 873 documents on big data and performance carrying out an extensive bibliometric analysis using two main techniques, i.e. performance analysis and science mapping. Findings Results point to a significant increase in the number of publications on big data and performance, highlighting a shortage of studies on business, management and accounting areas, and on how big data can improve performance measurement. Future research opportunities are identified. They regard the development of further research to explain how performance measurement field can effectively integrate big data into a PMS and describe the main themes related to big data in performance measurement literature. Originality/value This paper gives a holistic view of big data and performance measurement research through the inclusion of numerous contributions on different research streams. It also encourages further study for developing concrete tools.

scholarly journals Bank performance variability and strands of inflationary conditions

2020 ◽  
Vol 29 (3) ◽  
pp. 235-253
Author(s):  
Rexford Abaidoo ◽  
Hod Anyigba
Keyword(s):  
Performance Indicators ◽  
Banking Sector ◽  
Key Performance Indicators ◽  
Bank Performance ◽  
Inflation Expectations ◽  
Content Type ◽  
Return On Equity ◽  
Macroeconomic Conditions ◽  
Macroeconomic Uncertainty ◽  
The Us

PurposeThis study seeks to examine the extent to which strands of inflationary related conditions (inflation expectations, inflation uncertainty and realized inflation); macroeconomic uncertainty and the likelihood of recessionary conditions influence performance indicators in the US banking sector over a specified time period.Design/methodology/approachThe study adopts seemingly unrelated regression model (SUR) advanced by Zellner (1962) in its examination of how specific strands of inflationary conditions, and other adverse macroeconomic conditions influence performance dynamics in the US banking sector.FindingsEmpirical evidence suggest that among various adverse macroeconomic conditions examined, inflation expectations and macroeconomic uncertainty tend to have significant constraining impact on key performance indicators in the US banking sector than other conditions examined. Comparatively, this study finds that inflation expectations and macroeconomic uncertainty tend to have much more constraining impact on return on equity, than on return on assets in the US banking sector. Results further suggest that among the three bank performance indicators examined, net interest margin is the least vulnerable bank performance indicator to various adverse macroeconomic conditions examined in the study.Practical implicationsApart from the various empirical results noted above, this study's findings are projected to help inform strategic planning decisions among institutions in the banking sector. The various findings could, for instance, inform policies and operational strategies geared toward reducing vulnerability associated with specific performance indicators such as return on equity. This reduction could be achieved by critically examining how the various performance indicators react to individual adverse macroeconomic conditions examined in this study. The process could ultimately help in developing tailored measures/procedures aimed at reducing how susceptible key performance indicators are to the various adverse macroeconomic conditions. This study's findings could also provide the platform for more adaptive policies aimed at minimizing the effects of noted macroeconomic conditions on operational efficiency in the banking sector.Originality/valueThe uniqueness of this study, compared to related ones found in the literature, stems from its treatment of three variant of related strands of macroeconomic condition (different variant of inflationary conditions) in the same framework in its empirical analysis.

Help chain in companies undergoing a lean implementation

2018 ◽  
Vol 9 (1) ◽  
pp. 113-132 ◽  
Author(s):  
Guilherme Tortorella ◽  
Diego Fettermann
Keyword(s):  
Performance Indicators ◽  
Success Factors ◽  
Operational Performance ◽  
Quality Performance ◽  
Lean Implementation ◽  
Content Type ◽  
Critical Success ◽  
The Subject ◽  
And Performance ◽  
Validated Instrument

Purpose The purpose of this paper is to propose an instrument for assessing the relationships between the critical success factors (CSFs) that promote help chain, providing means to enhance overall equipment effectiveness (OEE) and quality performance in companies undergoing a lean implementation. Design/methodology/approach The aforementioned relationships were determined and validated through a survey carried out with 50 Brazilian manufacturers. The authors, thus, provide an empirically validated instrument for assessing help chain CSFs and their impact on key operational performance indicators with no parallel in the existing literature. Quality (incidence of scrap and rework in manufacturing processes) and OEE (overall equipment effectiveness measured in percentage) were chosen as performance indicators because of their recognized relevance in previous research related to help chain approach. Findings The results of this paper show that the size of the company and CSFs have a significant relationship with quality. However, for OEE, time of lean implementation seems to be significantly important to predict its performance. Originality/value Identifying relevant relationships between CSFs and performance indicators may contribute to specify the context in which problems are expected to occur. With that knowledge, manufacturers will be able to emphasize the development of such factors that tend to improve their operational performance. Therefore, possible correlations are investigated to obtain a clearer comprehension around the subject and enable a better understating over the boundary conditions that surround the problem.

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