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Responding to the radical changes in work practices and extensive virtual forms of interaction brought by COVID-19, this study aims to investigate the role played by authentic leadership and horizontal collectivism in helping the Indian startups sail through the pandemic.

Data was gathered through standardized questionnaires from 300 leaders and 300 employees from Indian startups during the second phase of lockdown. Statistical analysis using AMOS 23.0 checks for the direct effect of authentic leadership on work engagement and the moderating effect of horizontal collectivism on the relationship between the two. This study also compares the results between self-ascribed and perceived authentic leadership.

Statistical analysis using AMOS 23.0 was done to check for the direct effect of authentic leadership on work engagement and the moderating effect of horizontal collectivism on the relationship between authentic leadership and work engagement. This study also compared the results between self-ascribed and perceived authentic leadership.

To the best of the authors’ knowledge, this is the first study that explores the role of authentic leadership in unlocking work engagement among employees serving in Indian startups during the pandemic. The lesson learned from this is when employees perceived their leaders to be authentic, the work culture to be nonhierarchical and felt collective responsibility toward work, it unlocked their high potential and made them soulfully engaged in their work.

The purpose of the study was to find out the effect of authentic leadership on innovative work behavior among employees in the context of Indian startups that have gone global in the past one decade. The study also aimed to investigate the mediating effect of one organizational-level variable, i.e. organizational climate and one individual-level variable, i.e. readiness for change on the direct relationship between authentic leadership and innovative work behavior.

The study used survey method with a sample of 261 employees working in Indian startups that have gone global in the past one decade. Authentic leadership, organizational climate, readiness for change and innovative work behavior were measured using standardized questionnaires.

Structural equation modeling revealed that authentic leadership had significant direct effect on innovative work behavior and this effect was mediated by readiness for change. However, organizational climate had no significant effect.

The findings of the study have important implications for startups that employ millennials as employees and have plans to go global. Millennials have very different characteristics in the workplace and they regard authenticity in the leader very highly. Since they are assertive and they question everything, it becomes imperative for founder-leaders to exhibit authenticity in their actions, words and thoughts.

This is the first study in the context of Indian startups that have gone global by taking important variables of authentic leadership, readiness for change and innovative work behavior.

This study seeks to understand the connection of methodology by finding relevant papers and their full review using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA).

Concrete-filled steel tubular (CFST) columns have gained popularity in construction in recent decades as they offer the benefit of constituent materials and cost-effectiveness. Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Gene Expression Programming (GEP) and Decision Trees (DTs) are some of the approaches that have been widely used in recent decades in structural engineering to construct predictive models, resulting in effective and accurate decision making. Despite the fact that there are numerous research studies on the various parameters that influence the axial compression capacity (ACC) of CFST columns, there is no systematic review of these Machine Learning methods.

The implications of a variety of structural characteristics on machine learning performance parameters are addressed and reviewed. The comparison analysis of current design codes and machine learning tools to predict the performance of CFST columns is summarized. The discussion results indicate that machine learning tools better understand complex datasets and intricate testing designs.

This study examines machine learning techniques for forecasting the axial bearing capacity of concrete-filled steel tubular (CFST) columns. This paper also highlights the drawbacks of utilizing existing techniques to build CFST columns, and the benefits of Machine Learning approaches over them. This article attempts to introduce beginners and experienced professionals to various research trajectories.

This research is associated with the real-time parameters of wide- and narrow-body aircraft to recognize the quantitative relationship framework. This paper aims to find the superiority of aircraft design technology which triggers the reduction in specific fuel consumption (SFC) and economic competitiveness.

The real case study is performed with 22 middle-of-the-market (MoM) aircraft. This paper develops a fuel burn mathematical model for mid-size transport aircraft by a multi-linear regression approach. In addition, sensitivity analysis is performed to establish the authentication of the fuel burn model.

The study reveals that the MoM aircraft would be the future aircraft design in terms of better fuel economy and carbon footprint. From the multi-regression analysis, it is observed that the logarithmic regression model is the best fit for estimating the SFC. Moreover, fineness ratio, aspect ratio, gross weight, payload weight fraction, empty weight fraction), fuel weight fraction, payload, wing loading, thrust loading, range, take-off distance, cruise speed and rate of climb are observed as the suitable parameters which provide the best fitness value as 0.9804.

Several existing literature reveals that a few research has been performed on the MoM aircraft with wide-body configuration. Moreover, mathematical modelling on the fuel consumption was insignificantly found. This study examines several parameters which affect the fuel consumption of a wide-body aircraft. A real-case study for design configurations, propulsive systems, performance characteristics and structural integrity parameters of 22 different MoM aircraft are performed. Moreover, multi-regression modelling is developed to establish the relation between SFC and other critical parameters.

In the event of a disaster, educational institutions like schools serve as lifeline buildings. Hence, it is crucial to safeguard these buildings for the communities that may depend on the school as a disaster shelter and aid center. Thus, this paper aims to conduct a multihazard risk assessment survey at 50 schools (with 246 building blocks) in Dehradun.

The past few decades have witnessed the impact of multihazard frequency in Uttarakhand, India, due to the geographical features of the Himalayas and its neo-tectonic mountain-building process. Dehradun is the capital of Uttarakhand state and comes under seismic zone IV, which is highly prone to earthquakes.

The hazard assessment is divided into two types of surveys: first, building-level surveys that include rapid visual screening, nonstructural risk assessment and fire safety audit, and second, campus-level surveys that include vulnerability analysis for earthquake, flood, industrial hazard, landslide and wind.

This paper will list several gaps and unrecognized practices in the region that increase the schools’ multihazard risk. The study’s outcome will help prioritize the planning of disaster awareness, retrofitting execution, future construction practices and decision-making to minimize the risk and prepare the school for the upcoming disasters.

Physical data were collected by the author to determine the multihazard risk analysis in 50 schools in the Dehradun District of Uttarakhand, India. The building- and campus-level surveys have been used to generate a database for the retrofit and renovation process for each individual school to use their budget fruitfully and in a planned way. The survey conducted is more effort and a more detailed risk evaluation which necessitates effectively mitigating and ensuring the potential safety of the region’s schools.

Product counterfeiting has been ubiquitously observed in various segments of the supply chain. The intrinsic values of brands create more opportunities for counterfeiting. The damaging reputation of such brands leaves them to deal with the fallouts of counterfeits. Hence, such companies address them mainly through legal action, price and quality strategy. However, consumer characteristics and the random distribution of counterfeit products to the consumer types affect the effectiveness of a counter strategy. This paper aims to generate insights on how to leverage digital technology to curb counterfeit entities with consideration of consumer characteristics and the random distribution of counterfeits to them.

The authors used game theory and vertical differentiation model to understand and encounter deceptive counterfeiting of brand products. The study understands the economic relationship between a brand product manufacturer and consumer types based on their awareness. Further, the authors have considered different cases in the model to gain useful insights.

The results reveal that when the consumers are proactive, informed and value-conscious brand product manufacturers take digital technology counterstrategy to earn the maximum revenue. Hence, this analysis highlights that the effectiveness of a counterstrategy critically depends on the consumer characteristics, whether they are proactive, informed or unaware.

The study outlines that brand product manufacturers must emphasize on the digital supply chain, product redesign and product tracking facility to empower informed and value-conscious and proactive consumers. Moreover, the government should take steps to create awareness among uninformed consumers via information campaigns.

This paper incorporates the role of consumers and brand product manufacturers to understand and address the deceptive counterfeiting issue.

Agile practices are important for executing business dealings proficiently in today’s scenario, as they thrust on implicating strategies for meeting quick market requirements. These practices are noteworthy from the point of competitiveness and for fulfilling customer’s demands speedily and promptly. The purpose of this paper is to appraise agile supplier selection dilemma based on analytical hierarchy process (AHP), which accompanied grey information. The authors drafted a group of momentous agile supplier selection measures, which can be utilized by the group of industrial and manufacturing industries to measure the status of agile parameters in their partner firms. G-TOPSIS approach to handling the case of agile supplier selection problem is presented by the authors in this work.

The conception of AHP, grey theory and TOPSIS techniques is fused in this study, under the application arena of agile supply chain management (ASCM). The AHP principals are implicated in the first phase to define the priority importance weights of agile measures and, additionally, grey theory and TOPSIS principals are fused in the second phase to fabricate a significant agile supplier selection model.

A merged approach accompanying multiple measures is developed for aiding decision making and for modeling qualitative characteristics of agile arena under grey domain. The present work can be utilized to access the agile performance characteristics of the organization and can define the status of their partner suppliers. The technical guidelines of AHP and G-TOPSIS approach are explained in this study to be implicated in distinguish decision fields. An educational podium for dispensing the theoretical knowledge on supply chain management, ASCM and agility is presented in this study.

A second-level hierarchical structure is built by the authors to facilitate the managers in taking effective decision pertaining to agile measure in their organizations. The lists of qualitative characteristics are catalogued from the literature review in this study. The built model can undertake risk associated in defining the nature of agile criterions as grey concept can undertake risk associated with the system. Thus, the authors implicated G-TOPSIS approach to handling the case of agile supplier selection problem in this study. The presented hierarchical structure will capably assist the industrial and manufacturing firms to react toward random and unpredictable market requirements, along with attaining organizations goals and profits.

Currently, digital technology has been proposed as a new archetype for developing an effective traceability system in the perishable food supply chain (FSC). Implementation of such a system needs significant investment and the burden lies with the members of the supply chain. The purpose of this paper is to examine the impact on the profit of the supply chain members due to the implementation of an effective traceability system with such a large investment. The study also tries to explore the impact of the implementation of such a system by coordination among the members through a cost-sharing mechanism.

A two-level supply chain that comprises a supplier and retailer is analyzed using a game-theoretic approach. The mathematical models are developed considering the scenario for an individual, centralized and both members invest using a cost-sharing mechanism. For each of the models, the impact of product selling price, information sensing price and quality improvement level on profit is analyzed through numerical analysis.

The study reveals that consumer involvement can be a strong motivation for the supply chain members to initiate investment in the traceability system. Further, from an investment perspective cost-sharing model is beneficial compared to the individual investment-bearing model. This mechanism can coordinate as well as benefit the FSC members. However, the model is less beneficial to the centralized model from profit and quality improvement levels.

Food wastage can be less from supplier and retailer perspectives. Moreover, consumers can purchase food items only after verifying their shipping conditions. Consequently the food safety scandals can be reduced remarkably.

Digital technology adoption in the perishable FSC is still considered emerging. The present study helps organizations to implement a traceability system in the perishable FSC through consumer involvement and a cost-sharing mechanism.

Supply chain management (SCM)-embedded valuable resources, such as capital, raw-materials, products, partners, customers and finished inventories, where the evaluation of environmental texture and flexibilities are needed to perceive sustainability. The present study aims to identify and evaluate the directory of green and agile (G-A) attributes based on decision support framework (DSF) for identifying dominating measures in SCM.

DSF is developed by exploiting generalized interval valued trapezoidal fuzzy numbers (GIVTFNs). Two technical approaches, i.e. degree of similarity approach (DSA) and distance approach (DA) under the extent boundaries of GIVTFNs, are implicated for data analytics and for recognizing constructive G-A measures based on comparative study for robust decision. A fuzzy-based performance indicator, i.e. fuzzy performance important index (FPII), is presented to enumerate the weak and strong G-A characteristics to manage knowledge risks in allied business environment.

The modeling is illustrated from the insights of decision-makers for augmenting business value based on cognitive identification of measures, where the best performance score is identified by the “sustainable packaging” under the traits of green supply chain management (GSCM). “The use of Web-based applications” under the traits of agile supply chain management (ASCM) and “Outsourcing flexibility” under traits of ASCM is found as the second and third most significant performance characteristics for business sustainability. Additionally, the “Reutilization (recycling) and reprocessing” under GSCM in manufacturing and “Responsiveness and speed toward customers needs” under ASCM are found difficult in attainment.

The G-A evaluation will assist in attaining performance excellence in day-to-day operations and overall functioning. The outcomes will help executives to plan strategic objectives and attaining success.

To reinforce the capabilities of SCM, wide extent of G-A dimensions are presented, concept of FPII is reported to manage knowledge risks based on identification of strong attributes and two technical approaches, i.e. DSA and DA under GIVTFNs are presented for attaining robust decision and directing managerial decision-making process.