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1 – 10 of 40Nicola Castellano, Roberto Del Gobbo and Lorenzo Leto
The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on…
Abstract
Purpose
The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.
Design/methodology/approach
The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.
Findings
The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.
Practical implications
The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.
Originality/value
This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.
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Maria Elisabete Duarte Neves, Maria do Castelo Gouveia, Adriana Martins and Joaquim Carlos da Costa Pinho
The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF).
Abstract
Purpose
The main goal of this paper is better understand the risk/return trade-off of investing in socially responsible investment funds (SRIF) and green investment funds (GIF).
Design/methodology/approach
To achieve our aim a green investment fund portfolio, a socially responsible investment portfolio and a conventional fund (CF) portfolio from the United States of America (USA) were selected to compare the efficiency of these three different portfolios, by using Value-Based Data Envelopment Analysis (DEA) methodology.
Findings
The results point out that SRIF and GIF are more efficient than CF. For five years, the CFs have not outperformed the GIF.
Originality/value
The results suggest that there is a growing awareness on the part of investors that sustainable companies are the companies that will allow a better quality of life and a more sustainable environment. It seems that somehow managers and investors are aware that the market will compensate them for thinking about a cleaner and more equitable world.
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João Eduardo Sampaio Brasil, Fabio Antonio Sartori Piran, Daniel Pacheco Lacerda, Maria Isabel Wolf Morandi, Debora Oliveira da Silva and Miguel Afonso Sellitto
The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.
Abstract
Purpose
The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.
Design/methodology/approach
The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.
Findings
The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.
Practical implications
Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.
Originality/value
This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.
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Amir Yaqoubi, Fatemeh Sabouhi, Ali Bozorgi-Amiri and Mohsen Sadegh Amalnick
A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical…
Abstract
Purpose
A growing body of evidence points to the influence of location and allocation decisions on the structure of healthcare networks. The authors introduced a three-level hierarchical facility location model to minimize travel time in the healthcare system under uncertainty.
Design/methodology/approach
Most healthcare networks are hierarchical and, as a result, the linkage between their levels makes it difficult to specify the location of the facilities. In this article, the authors present a hybrid approach according to data envelopment analysis and robust programming to design a healthcare network. In the first phase, the efficiency of each potential location is calculated based on the non-radial range-adjusted measure considering desirable and undesirable outputs based on a number of criteria such as the target area's population, proximity to earthquake faults, quality of urban life, urban decrepitude, etc. The locations deemed suitable are then used as candidate locations in the mathematical model. In the second phase, based on the proposed robust optimization model, called light robustness, the location and allocation decisions are adopted.
Findings
The developed model is evaluated using an actual-world case study in District 1 of Tehran, Iran and relevant results and different sensitivity analyses were presented as well. When the percentage of referral parameters changes, the value of the robust model's objective function increases.
Originality/value
The contributions of this article are listed as follows: Considering desirable and undesirable criteria to selecting candidate locations, providing a robust programming model for building a service network and applying the developed model to an actual-world case study.
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Dhawal Sharad Jadhav and Subrat Sarangi
Over the past years, business strategies have been designed to improve ‘firms' financial and non-financial performances and achieve sustainable development, leading to corporate…
Abstract
Purpose
Over the past years, business strategies have been designed to improve ‘firms' financial and non-financial performances and achieve sustainable development, leading to corporate sustainability. This article is a bibliometric analysis of two decades of the relationship between corporate sustainability and firm performance, identifying the research focus and the gaps for future research.
Design/methodology/approach
The bibliometric review of corporate sustainability and performance research is between January 2004 and June 2023. As per the Web of Science database, the theme's research commenced around 2004, growing gradually till 2023. Five hundred thirty-nine published articles by peer-reviewed ABDC-indexed A and A* journals in English have been reviewed. The bibliometrix package in R software is used with VOSviewer for the bibliometric analysis.
Findings
The study's findings indicate a lack of research on the theme from developed and underdeveloped nations. Further, the analysis reveals five clusters of research: (1) business sustainability, (2) corporate sustainability reporting, (3) corporate sustainability, strategy, and innovation, (4) stakeholder and corporate sustainability, and e) corporate sustainability assessment.
Originality/value
The future research areas proposed are on two major themes, namely, corporate sustainability and organizational competitive advantage, including sub-themes such as “Environmental, Social, and Governance (ESG) and financial performance” and “greenhouse-gas emissions” and “market orientations,” respectively. There is a need for more research in developing markets, a comprehensive definition of corporate sustainability, and further exploration of the theme linking strategy and innovation.
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Shatakshi Bourai, Rahul Arora and Neetu Yadav
The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study…
Abstract
Purpose
The study aims to analyze factors impacting firms’ success and persistence in a digital platform competition using the structure-conduct-performance (SCP) framework. The study also includes real-life cases that are beneficial to academicians and practitioners to understand and develop strategies for success and persistence during uncertainty.
Design/methodology/approach
A literature review to identify the factors that impact success and persistence in a digital platform competition was conducted following Webster and Watson (2002). Findings were integrated into a SCP framework to examine and understand the identified factors’ relational impact.
Findings
While analyzing factors under the SCP framework, all factors were divided into three categories: those impacting positively, those impacting negatively and those with ambiguous impact on the success and persistence in digital platform competition. Digital platform firms can exploit the positively impacting factors to increase market share by being distinctive from other digital platform firms and becoming dominant by withstanding competition. On the other hand, negatively impacting factors increase barriers to entry, intensify competition and reduce the distinctiveness of digital platform firms. Lastly, a few factors may have either a positive or a negative impact depending upon the particular characteristics of the firm/industry.
Research limitations/implications
The study opens the scope for future research on empirically testing the developed conceptual framework and relationships by developing propositions to posit the possible impact of these factors on digital platforms’ success and persistence.
Originality/value
The study contributed to the existing literature by using SCP framework to analyze the factors affecting firm’s success and persistence in a digital platform competition. Also, the study has discussed the relational impact of factors rather than their impact in isolation.
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Mohd Azrai Azman, Zulkiflee Abdul-Samad, Boon L. Lee, Martin Skitmore, Darmicka Rajendra and Nor Nazihah Chuweni
Total factor productivity (TFP) change is an important driver of long-run economic growth in the construction sector. However, examining TFP alone is insufficient to identify the…
Abstract
Purpose
Total factor productivity (TFP) change is an important driver of long-run economic growth in the construction sector. However, examining TFP alone is insufficient to identify the cause of TFP changes. Therefore, this paper employs the infrequently used Geometric Young Index (GYI) and stochastic frontier analysis (SFA) to measure and decompose the TFP Index (TFPI) at the firm-level from 2009 to 2018 based on Malaysian construction firms' data.
Design/methodology/approach
To improve the TFPI estimation, normally unobserved environmental variables were included in the GYI-TFPI model. These are the physical operation of the firm (inland versus marine operation) and regional locality (West Malaysia versus East Malaysia). Consequently, the complete components of TFPI (i.e. technological, environmental, managerial, and statistical noise) can be accurately decomposed.
Findings
The results reveal that TFP change is affected by technological stagnation and improvements in technical efficiency but a decline in scale-mix efficiency. Moreover, the effect of environmental efficiency on TFP is most profound. In this case, being a marine construction firm and operating in East Malaysia can reduce TFPI by up to 38%. The result, therefore, indicates the need for progressive policies to improve long-term productivity.
Practical implications
Monitoring and evaluating productivity change allows an informed decision to be made by managers/policy makers to improve firms' competitiveness. Incentives and policies to improve innovation, competition, training, removing unnecessary taxes and regulation on outputs (inputs) could enhance the technological, technical and scale-mix of resources. Furthermore, improving public infrastructure, particularly in East Malaysia could improve regionality locality in relation to the environmental index.
Originality/value
This study contributes to knowledge by demonstrating how TFP components can be completely modelled using an aggregator index with good axiomatic properties and SFA. In addition, this paper is the first to apply and include the GYI and environmental variables in modelling construction productivity, which is of crucial importance in formulating appropriate policies.
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Kristijan Breznik, Naraphorn Paoprasert, Klara Novak and Sasitorn Srisawadi
This study aims to identify research trends and technological evolution in the polymer three-dimensional (3D) printing process that can effectively identify the direction of…
Abstract
Purpose
This study aims to identify research trends and technological evolution in the polymer three-dimensional (3D) printing process that can effectively identify the direction of technological advancement and progress of acceptance in both society and key manufacturing industries.
Design/methodology/approach
The Scopus database was used to collect data on polymer 3D printing papers. This study uses bibliometric approach along with network analytic techniques to identify and discuss the most important countries and their scientific collaboration, compares income groups and analyses keyword trends.
Findings
It was found that top research production results from heavy investments in research and development. The USA has the highest number of papers among the high-income countries. However, scientific production in the other two income groups is strongly dominated by China and India. Keyword analysis shows that countries with lower incomes in certain areas, such as composite and bioprinting, have fallen behind other groups over time. International collaborations were suggested as mechanisms for those countries to catch up with the current research trends. The evolution of the research field, which started with a focus on 3D printing processes and shifted to printed part designs and their applications, was discussed. The advancement of the research topic suggests that translational research on polymer 3D printing has been led mainly by research production from higher-income countries and countries with large research and development investments.
Originality/value
Previous studies have conducted performance analysis, science mapping and network analysis in the field of 3D printing, but none have focused on global research trends classified by country income. This study has conducted a bibliometric analysis and compared the outputs according to various income levels according to the World Bank classification.
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Taha Ahmad Jaber and Sabarina Mohammed Shah
This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the…
Abstract
Purpose
This study aims to identify the publication phase, performance and scientific contributions of research papers related to enterprise risk management (ERM) and to visualise the emerging themes in addressing volatility, uncertainty, complexity and ambiguity (VUCA).
Design/methodology/approach
The biblioshiny technique based on the bibliometrix R package was used to draw journal papers’ performance and scientific contributions by displaying distinctive features from the bibliometric method used in prior studies. The data was extracted from the Web of Science (WOS) and Scopus databases.
Findings
Since the 1990s, ERM publication has gained momentum, and it is generally categorised into four main themes. Studies by Miller (1992) and Bromiley et al. (2015) scored the highest in global and local citations, respectively. However, the Economic Outlook ranked first in quality of publications while the Journal of Risk and Insurance topped in quantity of publications. Collaborative research mainly exists between two authors, and the dynamic number of collaborative networks is evident in the USA.
Research limitations/implications
This study is limited by the filtered keywords used to generate the search on journal papers’ in WOS and Scopus. It is imperative to have more comprehensive and rigorous analytics on ERM research to enable a direction for future research. Finally, ERM implementation better equips firms to mitigate risk in a VUCA environment.
Originality/value
This study attempts to fill a vacuum of ERM literature, specifically in business economics, in addressing VUCA. Moreover, it covers a comprehensive predetermined period of from its inception in 1983 until 2022.
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Thyago Celso Cavalcante Nepomuceno, Miguel Gomes da Silva, Maria Eugênia Vergilio Mori, Wilka Maria do N. Silva and Isaac Pergher
The recent increase in the number of infections and mortality rates in many regions has emphasized the cyclical nature of this pandemic, with new variants emerging constantly…
Abstract
Purpose
The recent increase in the number of infections and mortality rates in many regions has emphasized the cyclical nature of this pandemic, with new variants emerging constantly. Understanding what has been done by efficient administrations to contain the outbreak is essential while new immunization developments for the new variants are not available.
Design/methodology/approach
This work adapts the traditional Banker, Charnes and Cooper (BCC) Variable Returns to Scale model for including panel data on the Brazilian Federal Government spending over the first pandemic months in Pernambuco to identify efficient municipalities and conduct a benchmark on the best practices, reactions and implications that can serve as a guide for the post-Covid recurrence era.
Findings
The results provide an interesting panorama of municipal response to the pandemic and some quantitative and qualitative prospects on potentials for improvements from the perspective of efficient and inefficient cities. Only one administration (São Bento do Una) was identified as efficient for the entire period. The authors’ benchmark and discussion are focused on this municipality.
Originality/value
The authors believe this work has two innovative components. The first is a robust and systematic methodology integrating the advances in testing convexity and returns to scale in the construction of a production frontier based on panel data. The second is a discussion on what drives efficiency (benchmarking of best practices) in addition to how to quantitatively attain such efficiency prospects. To the best of the authors’ knowledge, both methodological and empirical implications are original to the present manuscript.
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