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Organizational resilience is a prerequisite to ensure preparedness and quick recovery from disruptions for an organization. However, there is scant literature that examines antecedents that are associated with resilience. This study aims to evaluate antecedents of organizational resilience considering three factors: sustainable supply chain management (SSCM), business model adaptation (BMA) and digitalization.

This study considers the dynamic capability view as a theoretical lens to formulate the hypotheses between the mentioned constructs. The authors test the hypotheses based on the data collected from 259 manufacturing companies. The authors consider structural equation modeling and mediation analysis to analyze the proposed hypotheses.

The results of structural equation modeling suggest that there is a positive association between SSCM and organizational resilience. Furthermore, the results suggest that digitalizing the business processes and deploying an adaptable business model can help organizations enhance their resilience levels.

This study contributes to the literature by identifying dynamic capabilities that can influence organizational resilience and extending the relevance of BMA and digitalization in the context of sustainability and resilience. Furthermore, this research informs managers on effective pathways for managing future disruptions.

The Gulf Cooperation Council (GCC) of countries has some of the highest electricity consumptions and carbon dioxide emissions per capita in the world. This poses a direct challenge to the GCC government’s ability to meet their CO₂ reduction targets. In this review paper the current household electricity consumption situation in the GCC is reviewed.

Three scenarios for reducing energy consumption and CO₂ emissions are proposed and evaluated using strengths, weaknesses, opportunities and threats (SWOT) as well as the political, economic, social, technical, legal and environmental (PESTLE) frameworks.

The first scenario found that using solar Photovoltaic (PV) or hybrid solar PV and wind system to power household lighting could save significant amounts of energy, based on lighting making up between 8% to 30% of electricity consumption in GCC households. The second scenario considers replacement of conventional appliances with energy-efficient ones that use around 20% less energy. The third scenario looks at influencing consumer behavior towards sustainable energy consumption.

Pilot trials of these scenarios are recommended for a number of households. Then the results and feedback could be used to launch the schemes GCC-wide.

The proposed scenarios are designed to encourage responsible electricity consumption and production within households (SDG12).

All three proposals are found viable for policymakers to implement. However, to ensure successful implementation GCC Governments are recommended to review all the opportunities and challenges associated with these schemes as laid out in this paper.

The use of renewable energy has become necessary because of the harmful effects of current energy sources on the environment, limited availability and financial crisis. Transparent solar panels have emerged as a promising technology for integrating renewable energy generation into building structures. Therefore, this paper aims to explore the feasibility of transparent solar panels for high-rise building façades in Sri Lanka.

The research apprehended a qualitative approach, including two expert interview rounds adhering to the Delphi technique with 17 and 15 experts each per round. Manual content analysis was incorporated to analyse the collected data.

Regarding operation and maintenance, the study emphasizes the importance of regular inspection, cleaning and repair of transparent solar panels to ensure optimal performance and longevity. These activities contribute to maximizing energy generation and maintaining the aesthetic appeal of the building. The benefits of implementing transparent solar panels on building façades are manifold. They include renewable energy generation, reduced greenhouse gas emissions, improved energy efficiency and enhanced architectural aesthetics. Furthermore, the research findings underscore the potential of transparent solar panels to contribute to Sri Lanka’s sustainable development goals and address the country’s increasing energy demand. However, the study also identifies challenges that need to be addressed for successful implementation.

This study contributes to understanding the feasibility of transparent solar panels for high-rise building façades in Sri Lanka. The research findings offer valuable insights into the operation and maintenance aspects, benefits, challenges and strategies for implementing transparent solar panels effectively. This knowledge can guide policymakers, architects and developers in making informed decisions regarding the integration of transparent solar panels, thereby promoting sustainable and energy-efficient building practices in Sri Lanka.

Africa has the most deaths from infections yet lacks adequate capacity to engage in vaccine development, production and distribution, the cornerstone of efficiently managing and eliminating several infectious diseases. Research has scarcely explored the role of institutional logics in vaccine development, production and distribution, collectively known as end-to-end vaccine manufacturing. This study aims to explore how institutional logics influence firms to engage in the vaccine manufacturing value chain in Africa.

We conducted multiple case study research using five vaccine manufacturing firms from four African countries in three regions. Qualitative interviews were conducted among 18 executives in 5 vaccine manufacturing firms.

We identified that the state, corporate and market institutional logics disparately influence the different parts of the vaccine manufacturing value chain. These institutional logics co-exist in a constellation that also shapes the organizational forms. Their constellation has dominant logics that guide behavior, while subdominant and subordinate logics influence behavior to a limited extent. The findings show that institutional logics are a function of contextual factors, such as historical events, technological changes and pandemics.

The study developed a typology that identifies vaccine manufacturing firm archetypes, institutional logics and their constellations underpinned by contextual factors. The findings have implications for firms and policymakers, as they may guide the end-to-end vaccine manufacturing interventions adapted for their regions.

The purpose of this study is to extract factors enabling the digital car sharing enterprises' supply chain resilience (SCR), to interpret different factor prioritizations in terms of industry representatives’ assessments and specialties, and to discuss the results by applying and comparing different ranking techniques.

To achieve the purpose, the factors were identified via an in-depth systematic literature review, and next, these factors were examined by industry representatives to gather the decision matrices, then analytic hierarchy process (AHP) and measuring attractiveness by a categorical based evaluation technique (MACBETH) were applied separately to model the decision problem, and finally the findings were interpreted with different participants’ perspectives.

The findings revealed that the AHP and MACBETH provide nearly identical rankings in terms of main factors by implying the significance of the triple bottom line of sustainability. Therefore, the economic, social, and environmental dimensions of sustainability should be accomplished to obtain a resilient digital car sharing enterprise supply chain. In addition, readiness and agility are the other important factors affecting the enterprises’ resilience, and finally, although digitalization seemed to be the least important one, its sub-factor emerged at the top of the ranking list.

Up to the authors’ knowledge, this is the first study in the literature that focuses on the SCR of car sharing companies, a particular type of digital enterprise, and uses AHP and MACBETH to examine the important factors that might affect the SCR of these companies. Practitioners should take the findings of both methods into account when evaluating the results and determine the short- and long-term strategies accordingly.

Powder bed additive manufacturing has recently seen substantial growth, yet consistently producing high-quality parts remains challenging. Recoating streaking is a common anomaly that impairs print quality. Several data-driven models for automatically detecting this anomaly have been proposed, each with varying effectiveness. However, comprehensive comparisons among them are lacking. Additionally, these models are often tailored to specific data sets. This research addresses this gap by implementing and comparing these anomaly detection models for recoating streaking in a reproducible way. This study aims to offer a clearer, more objective evaluation of their performance, strengths and weaknesses. Furthermore, this study proposes an improvement to the Line Profiles detection model to broaden its applicability, and a novel preprocessing step was introduced to enhance the models’ performances.

All found anomaly detection models have been implemented along with several preprocessing steps. Additionally, a new universal benchmarking data set has been constructed. Finally, all implemented models have been evaluated on this benchmarking data set and the effect of the different preprocessing steps was studied.

This comparison shows that the improved Line Profiles model established it as the most efficient detection approach in this study’s benchmark data set. Furthermore, while most state-of-the-art neural networks perform very well off the shelf, this comparison shows that specialised detection models outperform all others with the correct preprocessing.

This comparison gives new insights into different recoater streaking (RCS) detection models, showcasing each one with its strengths and weaknesses. Furthermore, the improved Line Profiles model delivers compelling performance in detecting RCS.

The primary purpose of this study is to examine the factors leading to shopping cart abandonment and construct a model depicting interrelationship among them using interpretive structural modeling (ISM) and Matriced Impact Croises Multiplication Appliquee an un Classement (MICMAC).

Initially, 20 factors leading to shopping cart abandonment were extracted through a systematic literature review and expert opinions. Fifteen factors were finalized using the importance index and CIMTC method, for which consistency has been checked in SPSS software through a statistical reliability test. Finally, ISM and MICMAC approach is used to develop a model depicting the contextual relationship among finalized factors of shopping cart abandonment.

The ISM model depicts a technical glitch (SC8), cash on delivery not available (SC4), bad checkout interface (SC9), just browsing (SC11), and lack of physical examination (SC12) are drivers or independent factors. Additionally, four quadrants have been formulated in MICMAC analysis based on their dependency and driving power. This facilitates technical managers of e-commerce companies to focus more on factors leading to shopping cart abandonment according to their dependency and driving power.

Taking an expert’s opinion as a base may affect the results of the study due to biases based on subjectivity.

This study’s outcomes would accommodate practitioners, researchers, and multinational or national companies to indulge in e-commerce to anticipate factors restricting the general public from online shopping.

For the successful running of an e-commerce business and to retain the confidence of e-shoppers, every e-commerce company must make a strategy for controlling factors leading to shopping cart abandonment at the initial stage. So, this paper attempts to highlight the main factors leading to shopping cart abandonment and interrelate them using ISM and MICMAC approaches. It provides a clear path to technical heads, researchers, and consultants for handling these shopping cart abandonment factors.

The current adverse changes in climatic conditions have necessitated innovative nature-based solutions like blue-green roofs to ensure sustainable built environments. The use of blue-green roofs in combating climate change issues has continued to grow, and its benefits are showcased in many countries' studies. However, there is an absence of reports on the use of this approach in South Africa. Therefore, in ensuring a sustainable built environment through nature-based solutions, this study explored the built environment professional’s knowledge of blue-green roofs, the hindrances to their use and motivations for much wider use of blue-green roofs in the country.

Based on the nature of the study, a quantitative design was adopted and data were obtained from professionals within the built environment through a questionnaire. Data analyses were conducted using the Cronbach alpha test, Kruskal–Wallis H-Test, exploratory factor analysis and fuzzy synthetic evaluation.

The findings revealed a growing knowledge of blue-green roofs, albeit its slow adoption in the country. Also, five critical clusters of hindrances affecting the use of blue-green roofs were identified. These are understanding the blue-green roof concepts, technical, economic, regulation and client hindrances. Furthermore, the ability to manage stormwater properly, provide climate change adaptation and deliver sustainable buildings were the key motivating factors that could drive the use of this innovative solution.

This study offers actionable insights for built environment professionals and stakeholders to address the hindrances to using blue-green roofs in South Africa. Strategies such as improved education, financial incentives and policy development can help overcome some notable hindrances and promote the widespread adoption of blue-green roofs.

The slow adoption of blue-green roofs and the scant nature of research within the built environment required adequate attention to which this current research contributes. Theoretically, being one of the foremost studies in South Africa to explore blue-green roofs, the findings offer a foundation for future studies seeking to explore this roofing system in the country further.

In this paper, a mixture of exponential and Rayleigh distributions in the proportions α and 1 − α and all the parameters in the mixture distribution are estimated based on fuzzy data.

The methods such as maximum likelihood estimation (MLE) and method of moments (MOM) are applied for estimation. Fuzzy data of triangular fuzzy numbers and Gaussian fuzzy numbers for different sample sizes are considered to illustrate the resulting estimation and to compare these methods. In addition to this, the obtained results are compared with existing results for crisp data in the literature.

The application of fuzziness in the data will be very useful to obtain precise results in the presence of vagueness in data. Mean square errors (MSEs) of the resulting estimators are computed using crisp data and fuzzy data. On comparison, in terms of MSEs, it is observed that maximum likelihood estimators perform better than moment estimators.

Classical methods of obtaining estimators of unknown parameters fail to give realistic estimators since these methods assume the data collected to be crisp or exact. Normally, such case of precise data is not always feasible and realistic in practice. Most of them will be incomplete and sometimes expressed in linguistic variables. Such data can be handled by generalizing the classical inference methods using fuzzy set theory.

Management innovation is one of the most vital practices underpinning economic growth and is considered to be one of the fundamental components of gaining a superior business position in market conditions that are continually fluctuating. Drawing upon neo-institutional theory as well as absorptive capacity, the current empirical study unpacks the relationships between external institutional forces (i.e. regulative, mimetic and normative pressures) and management innovation through investigating the role of absorptive capacity as a mediator.

The research model is tested using survey data from Australian organisations. The study used Partial Least Squares (PLS), a component-based structural equation modelling (SEM) method, in order to perform the data analysis.

The results confirm that the various dimensions of institutional forces have diverse influences on management innovation. The authors found mimetic and normative pressures have positive influences on realised and potential absorptive capacity of an organisation. In addition, realised absorptive capacity mediates the relations between institutional forces and management innovation.

Dissimilar to preceding studies, this research shows that organisations not only innovate to pursue higher performance but sometimes strive for legitimacy. In addition, the significant associations between absorptive capacity and management innovation and the mediation role clearly signify that institutional forces and absorptive capacity play significant roles in the adoption of management innovation.