Search results

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

The purpose of this study is to evaluate whether the classification of the equity mutual fund depends on the performance measure used.

The sample for this study includes stock mutual funds for the USA, Europe and emerging market economies covering the period 2010 to 2020. Using more than 20 performance measures the results are compared using the Sharpe ratio as the reference.

The results show that performance measures based on absolute reward–risk ratios like Sortino, Treynor, etc. have similar rankings, because in general the numerator (mean excess return) is the same. However, when the authors employ other types of performance measures, results may be significantly different, especially in the case of metrics for “incremental returns”, i.e. alphas. Focussing on markets, their results show that choosing performance measures is more relevant for emerging markets.

The sample is only limited to the USA, Europe and the emerging market, and there are other performance metrics in the literature which have not been covered in this work.

The ordering of equity mutual funds depends on the measure used, specially if investors employ factor models to measure excess returns (alphas). Hence, policy formulation on disclosure of mutual fund performance should encourage the use of several metrics from different families. Investors must be aware of the different rankings made and the most appropriate metrics based on their preferences.

This paper focusses specifically on the effect that performance metrics have on relative fund performance. Previous studies have ignored alpha metrics to rank funds, which are commonly employed by investors. The authors’ study performs an analysis for three different markets considering the two main developed ones (the American and European equity markets), as well as the emerging one, largely ignored until now.

ESG (Environment, Social, Governance) has taken on increased importance in recent years for all stakeholders, with the S dimension now taking on a stronger focus in the real estate space. This paper proposes a new metric to be used in the S space to assess improvements in aspects such as gender equality and cultural diversity in real estate. It adds to the S metrics currently available to see the more effective delivery of the S dimension into real estate investment decision-making.

A new S metric in ESG is proposed and validated. Using this metric, examples regarding gender equality and cultural diversity are assessed among leading real estate players in Australia. This S metric is assessed over a number of time periods to demonstrate the improvements in gender equality and cultural diversity in these major real estate players.

This new S metric is seen to be highly effective and robust in capturing the changes in various aspects of the S dimension in ESG in the real estate space today; particularly concerning gender equality and cultural diversity. It is clearly able to demonstrate the significant changes in increased participation of women at the more senior leadership levels by leading players in the real estate space.

With ESG becoming a critical issue in the real estate sector, issues involved in the S space will take on increased significance going forward. This is critical, as the elements of the S dimension such as gender equality and cultural diversity are important aspects for an effectively functioning real estate industry. The S metric developed in this paper can be used for benchmarking purposes over time, as well as between real estate players, between sub-sections within a real estate organisation, and comparing against other industry sectors. It is also relevant in all organisations, and is not just limited to the real estate sector. Additional metrics in the S space are an important development to further empirically assess the effective delivery of the S dimension of ESG in the real estate sector and more broadly.

This paper specifically proposes this new S metric in ESG in the real estate industry. This is a key issue for the real estate industry going forward at all levels, as it will facilitate a more diverse real estate industry and more effective real estate investment decision-making. This S metric is applicable in all organisational sectors where the S dimension of ESG is important.

Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.

Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.

According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.

The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.

This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.

The exact process of construction projects performance assessment and benchmarking still remains subjective relying on qualitative techniques, which does not allow stakeholders to address the issues and the drawbacks of their respective projects as effectively as possible for performance improvement purposes. Hence, this research aims to establish a unified project performance score (PPS) for assessing and comparing projects performance.

Data were collected from Construction Industry Institute (CII) members and through University of Wisconsin active research projects. Exploratory data analysis was done to investigate the calculated performance metrics and the collected data characteristics. Data were converted into six performance metrics which were used as the independent variables in creating the PPS model. Logistic regression model was developed to generate the unified PPS equation in order to explain the variables that significantly affect construction projects successful post-completion performance. The PPS model was then applied on the collected dataset to benchmark projects in terms of project delivery systems, compensation types and project types in order to showcase the PPS capabilities and possible applications.

The model revealed that construction cost and schedule growth are the most important metrics in assessing projects performance, while RFIs’ processing time and change orders per million dollars were the features with the least effect on the PPS value. The authors found that integrated project delivery (IPD) and target value (TV) projects outperformed all other project delivery and compensation types. While, industrial projects showed the worst performance, as compared to commercial or institutional projects.

The PPS model can be used to assess the performance of any pool of executed projects, and introducing a novel addition to the field of construction business analytics which is a supplementary tool to successful decision making and performance improvement. Additionally, the bidding selection system can be revolutionized from a cost-based to a performance based one using the PPS model to improve the outcomes of the buyout process.

The United Nations member countries adopted a set of 17 sustainable development goals (SDGs) to achieve a better and more sustainable future for all. It encourages the use of sustainable practices during new product development (NPD). Competitiveness has put pressure on organizations to maintain their market share and look for new approaches related to NPD. The current study aims to focus on creating a framework that can help to achieve the SDGs by adopting agile new product development (ANPD) practices and Industry 4.0 technologies.

From the literature, various ANPD practices, Industry 4.0 technologies, performance metrics, their interconnection and their contribution toward achieving SDGs are extracted. The weights of selected Industry 4.0–ANPD practices are computed by robust best worst method (RBWM), and the Fuzzy-VIKOR method is used to rank the selected performance metrics. To test the robustness of the developed framework, sensitivity analysis is also performed.

The results show that among the various Industry 4.0–ANPD practices “Multi-skilled employees” have the highest weight followed by “Customer requirement analysis and prioritization.” Whereas for performance metrics, “The number of innovative products launched per year” is ranked first, with the “Average time between two launches” at second place.

This research contributes to the adoption of ANPD practices and Industry 4.0 technologies for the achievement of the business SDGs. The shortlisted Industry 4.0–ANPD practices will help in resolving the social and environmental issues. The set of performance metrics will help practitioners and managers to evaluate the performance of ANPD in the context of business SDGs.

This study adds to the understanding related to Industry 4.0–ANPD practices adoption. And to the best of the authors’ knowledge, it is believed that no similar work has been done previously and by using industry insights into technology components, this work contributes to valuable insights into the subject.

Marketing professionals are under pressure to implement methods and metrics that demonstrate the value of the function. This paper aims to propose a model to measure marketing performance, focusing on four categories of metrics and two types of factors that influence the effectiveness of the assessment process.

The paper is organized in three parts. The first part includes a synthesis of the theoretical background on the subject. Next, the rationale and architecture of the model are presented, together with an explanation of the elements that compose it. A reflection on the work developed is presented in the last section.

Benefits regarding how to best assess marketing practice are considerable, as organizations with effective performance measurement systems tend to show better results than others. In this context, the choice of metrics is important, but it is also necessary to understand the mechanisms through which the effectiveness of the measurement process can be improved.

Literature has mainly focused attention on the effect of individual programs on specific measures or on conceptual models that do not sufficiently address all major elements in the marketing assessment process. This work extends previous contributions on the subject, presenting a model that combines metrics with factors underlying the measurement process.

The purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.

A Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.

The proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.

The model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.

Mamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

The purpose of this study is to investigate the factors facilitating and influencing the adoption of DevOps practices specifically tailored to mobile software development, with a focus on understanding the influence of mobile-specific requirements on DevOps integration.

The study employs a qualitative methodology, including a literature review, exploratory case research and partial quantitative assessments through DORA metrics and survey applications. This approach, guided by the Technology-Organization-Environment (TOE) framework, prioritizes in-depth insights into the adoption of DevOps practices and explores strategies for integrating DevOps in mobile software development.

The research identifies several key themes specific to Mobile DevOps adoption, including tool integration issues, testing complexities, deployment challenges and security concerns. These findings underscore the necessity for tailored DevOps solutions that can effectively address the unique demands of mobile software development. The study also proposes actionable strategies to overcome these challenges, thereby enhancing the efficiency, quality and security of mobile applications.

The insights gained from this study provide valuable guidance for practitioners in the mobile software development sector. By understanding and addressing the specific challenges of Mobile DevOps, organizations can improve their DevOps practices and achieve better outcomes in terms of project delivery speed, quality and security. For example, implementing robust testing strategies, investing in compatible tools and developing well-defined rollback procedures can significantly enhance Mobile DevOps effectiveness. Furthermore, incorporating continuous security measures and improving cross-functional collaboration can lead to more secure and efficient mobile application deployments.

This study offers valuable starting points for researching Mobile DevOps in real-world settings, based on insights from practical DevOps implementations in a single-case organization. Organizations can use this information to compare their own DevOps approaches with those of the studied organization, and can facilitate self-assessment and improvement.

This study contributes to the limited literature on Mobile DevOps adoption and proposing actionable strategies. By incorporating the TOE framework, it provides a comprehensive guide that enhances understanding and management of DevOps practices throughout the mobile application development lifecycle and offers significant value to practitioners and researchers alike.

This work conducts a comprehensive analysis of how to incorporate resilience and sustainability into capacity expansion strategies for business-to-business (B2B) chemical supply chains. This study aims to guide both researchers and managers on ensuring profitability in B2B chemical supply chains while minimizing environmental impacts, complying with regulations and mitigating disruptions and risks.

A systematic literature review is conducted to analyze the interplay between sustainability and resilience in chemical B2B supply chains, specify the quantitative and qualitative methods used to tackle this challenge and identify the drivers and barriers concerning capacity expansion. In addition, a comprehensive conceptual framework is suggested to outline a compelling research agenda.

The findings emphasize the increasing importance of modeling and resolving decision-making challenges related to sustainable and resilient supply chains, particularly in capital-intensive chemical industries. Yet, there is no standardized strategy for addressing these challenges. The predominant solution methods are heuristic and metaheuristic, and the selection of performance metrics tends to be empirical and tailored to specific cases. The main barriers to achieving sustainability and resilience arise from resource limitations within the supply chain. Conversely, the key drivers of performance focus on enhancing efficiency, competitiveness, cost effectiveness and risk management.

This work offers practitioners a conceptual framework that synthesizes the knowledge and tackles the challenges of designing sustainable and resilient supply chains as well as managing their operations in the context of B2B chemical supply chains. Results provide a practical guide for navigating the complex interplay of sustainability, resilience and chemical supply chain expansion.

The key concepts and dimensions associated with capacity expansion planning for a resilient and sustainable chemical supply chain are identified through structured and comprehensive analyses of existing literature. A conceptual framework is proposed for delineating the intersections among sustainability, resilience and chemical supply chain expansions. This mapping endeavor aims to facilitate a future characterized by the deployment of a nexus of resilience and sustainability in chemical supply chains. To this end, a promising future research agenda is accordingly outlined.