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The global environments that surround contemporary business activities are uncertain, fast-changing, and frequently exposed to abrupt unexpected events with the potential to inflict extreme impacts where the ability to respond and adapt the organization effectively becomes a primary strategic concern. However, various firms that operate across diverse industry contexts approach this adaptive challenge in distinct ways that lead to quite diverse outcomes with many negative performers and some high performers with positive risk features. The heterogeneous approaches appear to consistently form extreme left-tailed performance distributions with inverse risk-return features but we are not really able to explain why and how these regularly observed phenomena come about. Hence, we want to study these organizational artifacts by collecting an extensive updated dataset to test the proposed relationships, explore alternative explanations, and learn from the extreme exemplars often referred to as outliers. There are extensive literatures in (strategic) management and finance that have dealt with the distribution of firm returns from slightly different angles but with some emerging commonalities that can inspire further analyses of the performance data. As a precursor for this, we discuss the odds of effective strategic adaptation in complex dynamic environments and introduce resilience as a proper outcome when simple solutions are scarce, and consider conditions that may facilitate these aims. The premises for the ensuing analyses are laid out and the main contents of the following chapters are presented.

The purpose of the study is to establish a predictive model for sustainable wire electrical discharge machining (WEDM) by using adaptive neuro fuzzy interface system (ANFIS). Machining was done on Titanium grade 2 alloy, which is also nicknamed as workhorse of commercially pure titanium industry. ANFIS, being a state-of-the-art technology, is a highly sophisticated and reliable technique used for the prediction and decision-making.

Keeping in the mind the complex nature of WEDM along with the goal of sustainable manufacturing process, ANFIS was chosen to construct predictive models for the material removal rate (MRR) and power consumption (Pc), which reflect environmental and economic aspects. The machining parameters chosen for the machining process are pulse on-time, wire feed, wire tension, servo voltage, servo feed and peak current.

The ANFIS predicted values were verified experimentally, which gave a root mean squared error (RMSE) of 0.329 for MRR and 0.805 for Pc. The significantly low RMSE verifies the accuracy of the process.

ANFIS has been there for quite a time, but it has not been used yet for its possible application in the field of sustainable WEDM of titanium grade-2 alloy with emphasis on MRR and Pc. The novelty of the work is that a predictive model for sustainable machining of titanium grade-2 alloy has been successfully developed using ANFIS, thereby showing the reliability of this technique for the development of predictive models and decision-making for sustainable manufacturing.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.

The purpose of this study is to reveal the friction reduction performance and mechanism of granular flow lubrication during the milling of difficult-to-machining materials and provide a high-performance lubrication method for the precision cutting of nickel-based alloys.

The milling tests for Inconel 718 superalloy under dry cutting, flood lubrication and granular flow lubrication were carried out, and the milling force and machined surface quality were used to evaluate their friction reduction effect. Furthermore, based on the energy dispersive spectrometer (EDS) spectrums and the topographical features of machined surface, the lubrication mechanism of different granular mediums was explored during granular flow lubrication.

Compared with flood lubrication, the granular flow lubrication had a significant force reduction effect, and the maximum milling force was reduced by about 30%. At the same time, the granular flow lubrication was more conducive to reducing the tool trace size, repressing surface damage and thus achieving better surface quality. The soft particles had better friction reduction performance than the hard particles with the same particle size, and the friction reduction performance of nanoscale hard particles was superior to that of microscale hard particles. The friction reduction mechanism of MoS₂ and WS₂ soft particles is the mending effect and adsorption film effect, whereas that of SiO₂ and Al₂O₃ hard particles is mainly manifested as the rolling and polishing effect.

Granular flow lubrication was applied in the precision milling of Inconel 718 superalloy, and a comparative study was conducted on the friction reduction performance of soft particles (MoS₂, WS₂) and hard particles (SiO₂, Al₂O₃). Based on the EDS spectrums and topographical features of machined surface, the friction reduction mechanism of soft and hard particles was explored.

The purpose of this study to find an alternate method to minimize waste i.e., eggshell and rice husk ash. In this paper, eggshell (ES) and rice husk ash (RHA) particles are used as reinforcements for examining their effect on the coefficient of thermal expansion (CTE), grain size (GS) and corrosion behavior for developed composite material.

In this investigation, 5 Wt.% each of ES and RHA reinforcement particles have been introduced. To investigate the microstructures of the developed composite material, scanning electron microscope was used. Physical and mechanical properties of composite material are tensile strength and hardness that have been examined.

The result of this paper shows that number of grains per square inch for composition Al/5% ES/5% RHA composite was found to be 1,243. Minimum value of the volume CTE was found to be 6.67 × 10–6/°C for Al/5% ES/5% RHA composite. The distribution of hard phases of ES particles in metal matrix is responsible for improvements in tensile strength and hardness. These findings demonstrated that using carbonized ES as reinforcement provides superior mechanical and physical properties than using uncarbonized ES particles.

There are several articles examining the impact of varying Wt.% of carbonized ES and rice husk reinforcement on the microstructures and mechanical characteristics of metal composites. CTE, GS and corrosion behavior are among of the features that are examined in this paper.

This paper aims to conduct a fuzzy discrete time cost quality risk in the ambiguous mode CO_{2 tradeoff problem} (FDTCQRP*TP) in a megaproject based on fuzzy ground.

A combinatorial evolutionary algorithm using Fuzzy Invasive Weed Optimization (FIWO) is used in the discrete form of the problem where the parameters are fully fuzzy multi-objective and provide a space incorporating all dimensions of the problem. Also, the fuzzy data and computations are used with the Chanas method selected for the computational analysis. Moreover, uncertainty is defined in FIWO. The presented FIWO simulation, its utility and superiority are tested on sample problems.

The reproduction, rearrangement and maintaining elite invasive weeds in FIWO can lead to a higher level of accuracy, convergence and strength for solving FDTCQRP*TP fuzzy rules and a risk ground in the ambiguous mode with the emphasis on the necessity of CO₂ pollution reduction. The results reveal the effectiveness of the algorithm and its flexibility in the megaproject managers' decision making, convergence and accuracy regarding CO₂ pollution reduction.

This paper offers a multi-objective fully fuzzy tradeoff in the ambiguous mode with the approach of CO₂ pollution reduction.

Food insecurity is a major concern for developing economies. Operational inadequacies get introduced with unorganized interactions among stakeholders in the food supply chain, affecting social, economic, environmental and operational (SEEO) aspects of a nation. This study analyzes India's largest food safety net program, Public Distribution System (PDS) and develops a perception-based model, mapping the root causes (of food insecurity) with possible solutions. The novelty lies in leveraging blockchain in the implementation of food traceability system.

Soft system methodology (SSM) is used to identify and analyze problems in PDS, leveraging the learning and inquiry process. It relies on system thinking and action research to create a defendable and rational model, which helps in proposing recommendations for addressing the problem.

Blockchain-enabled food traceability system increases transparency, thus enabling the fulfillment of basic food necessities for beneficiaries.

The proposed model enables policymakers to build a profound understanding of existing operational issues and provides insightful recommendations for making informed decisions to deal with the grave issue of food insecurity.

Unlike previous studies, this research attempts to understand operational inefficiencies during interactions among stakeholders. It proposes a perception-based conceptual model for the final implementation at the ground level. It also reveals significance of three systems: a delivery system, an enabling system empowering delivery system and a criteria system to control and monitor processes. This study thus bridges an important gap in the literature by proposing a blockchain-driven traceability system, under the control of criteria system, through the integration of system-thinking and action-research approach.

The purpose of this paper is to evaluate the effect of titanium oxide (TiO₂) and yttrium oxide (Y₂O₃) nanoparticles-reinforced pure aluminium (Al) on the mechanical properties of hybrid aluminium matrix nanocomposites (HAMNCs).

The HAMNCs were fabricated via a vacuum die-assisted stir casting route by a two-step feeding method. The varying weight percentages of TiO₂ and Y₂O₃ nanoparticles were added as 2.5, 5, 7.5 and 10 Wt.%.

Scanning electron microscope images showed the homogenous dispersion of nanoparticles in Al matrix. The tensile strength by 28.97%, yield strength by 50.60%, compression strength by 104.6% and micro-hardness by 50.90% were improved in HAMNC1 when compared to the base matrix. The highest values impact strength of 36.3 J was observed for HAMNC1. The elongation % was decreased by increasing the weight percentage of the nanoparticles. HAMNC1 improved the wear resistance by 23.68%, while increasing the coefficient of friction by 14.18%. Field emission scanning electron microscope analysis of the fractured surfaces of tensile samples revealed microcracks and the debonding of nanoparticles.

The combined effect of TiO₂ and Y₂O₃ nanoparticles with pure Al on mechanical properties has been studied. The composites were fabricated with two-step feeding vacuum-assisted stir casting.

Social entrepreneurship (SE) is a complex phenomenon designed to resolve numerous societal challenges while remaining economically viable. However, how social entrepreneurs in developing countries have deployed digital technologies to address communal challenges during the Covid-19 crisis is largely undocumented. This research examines social entrepreneurs' adoption of digital technologies, the multi-level organisational conditions, and associated innovative outcomes of engaging digital technologies.

Based on the organisational resilience theoretical framework, this research employs a qualitative methodology, comprising 38 semi-structured interviews with Nigerian SE firms, to investigate social entrepreneurs' engagement with digital technologies.

The study’s findings reveal 19 pathways through which digital technologies enabled organisational resilience outcomes by Nigerian SE firms during the Covid-19 pandemic. This allows the authors to show, via a 3 × 3 matrix, how social entrepreneurs deploy digital technologies to build proximate, dynamic, and continuous resilience in a weak institutional context.

The study’s findings enables the authors to advance the SE – digital technologies – resilience scholarship in a developing economy.

Business environments and global transportation system have become more complex than ever due to complexity drivers of industries which create uncertainty and unpredictability to organizations. Like other industries, the maritime business faces different and difficult problems which threaten organizational survival. The ability to cope with those uncertainties, threats and problems shows the resilience ability of organizations that help to survive and prosper. The organizational resilience concept arises as a requirement to deal with problems and uncertainties of business environments which are swiftly changing. This study aims to suggest an organizational framework to show how maritime business organizations as the sea leg of global transportation system can develop resilient organizations via complex adaptive systems (CAS) approach if adequate design features of CAS could be defined and included in organizational properties.

A total of 15 CAS features were identified as the enablers of organizational resilience throughout the literature. An interpretive structural modeling (ISM) approach has been conducted to determine the mutual relation between the CAS features which constitute an organizational framework. These CAS features have been categorized by conducting MICMAC analysis.

This study proposes a framework that identifies CAS features as the enabler of resilient maritime business organizations. The CAS approach offers new managerial toolkit to realize current organizational situations and allows managers to understand that it is difficult to control their system in this dynamic environment where special management practices are required especially in volatile times rather than ordinary times. Also, organizations could not compete as a sole organization but as a web/system of organizations. CAS is more resilient than other systems because resilience is the emergent occurrence of the system formed from nonlinear, dynamic interactions with self-organized agents.

The research has some limitations, like organizational resilience studies are in the infant stage and further research into this area should be extended. This study uses the CAS approach to develop organizational resilience. Further studies could use different lenses and contemporary subjects in management field which should also be useful while developing resilience in organizations. This study uses ISM and MICMAC analysis where further studies could use quantitative design and methods like formal concept analysis or the decision making trial and evaluation laboratory to determine the relational weighs of CAS features while developing resilient organizations. Future studies may also focus on different maritime stakeholders like IMO or ILO, maritime agencies, freight forwarders or insurance underwriters regarding developing and enhancing resilience of the maritime system.

World trade and transportation systems are getting more uncertain and lean on complex relations where maritime transportation is a “vital backbone” of such operations. But becoming more complex structures leads to vulnerable systems and organizations. Most risk management applications are based on predicting the known risks where many of them are not enough to fight with unknowns. Coping with today's problems are difficult for organizations in any industry. But for maritime business stakeholders who work in such a global web of relations, it is much more challenging. So, stakeholders of the system like forwarders, ports or ship chandlers may easily apply those features to develop resilient organizations too. Legal authorities of the system and rule-makers like local Chambers of Shipping, IMO or Classification societies can benefit from this framework and provide supportive settings to develop system-wide resilient organizations.

By understanding environmental uncertainty and complexity better than others, organizations become resilient and cope with significant difficulties which make them more competitive as a substantial strategic advantage. Resilient management offers to break down points at the system and shows them ways to restore quickly while transporting goods while traditional risk assessments are not enough.

The originality of the study lies in two folds; first of all the key and most used features of CAS is linked to developing resilient maritime organizations and by maritime expert opinions, this study tries to determine which of these CAS features are the most effective to trigger other features to develop organizational resilience in the maritime business. And secondly, the concept of organizational resilience and the CAS approach are not analyzed in depth in the context of maritime business.