With an exponential increase in consumers' need for electronic products, the world is facing an ever-increasing economic and environmental threat of electronic waste (e-waste). To minimize their adverse effects, e-waste recycling is one of the pivotal factors that can help in minimizing the environmental pollution andto increase recovery of valuable materials. For instance, Printed Circuit Boards (PCBs), while they have several valuable elements, they are hazardous too; and therefore, they form a large chunk of e-waste being generated today. Thus, in recycling PCBs, Electronic Components (ECs) are segregated at first, and separately processed for recovering key elements that could be re-used. However, in the current recycling process, especially in developing nations, humans manually screen ECs, which goes on to affect their health. It also causes losses of valuable materials. Therefore, automated solutions need to be adopted for both to classify and to segregate ECs from waste PCBs. The study proposes a robust EC identification system based on computer vision and deep learning algorithms (YOLOv3) to automate sorting process which would help in further processing. The study uses a publicly available dataset, and a PCB dataset which reflect challenging recycling environments like lighting conditions, cast shadows, orientations, viewpoints, and different cameras/resolutions. The outcome of YOLOv3 detection model based on training of both datasets presents satisfactory classification accuracy and capability of real-time competent identification, which in turn, could help in automatically segregating ECs, while leading towards effective e-waste recycling.

This paper studies a collection centre location problem for e-waste acquisition from households. The proposed location-allocation model is a bi-objective mixed-integer non-linear model that maximises waste collection and minimises the cost of collection. The model considers that both drop-off and pick-up policies are in place, i.e., people can either drop their e-waste at a collection centre or request doorstep pick-up of their e-waste. The model considers that people ' s decision to drop off their e-waste at the collection centres depends on the financial incentive offered by the firm and the distance of the collection centre. However, in the case of pick-up, no incentive is provided, and it is considered that the households ' willingness to return depends on people's concern for environmental degradation. The proposed model decides the location of the collection centre, the assignment of customer nodes, the incentive offered, and the e-waste collected using both pick-up and drop-off methods. Instances generated using a real case of Delhi, India, demonstrate the feasibility and validity of the proposed model, and the epsilon constraint method is employed to handle its multi-objectivity. Furthermore, sensitivity analysis is used to assess the relative importance of the parameters on the model output. The study offers valuable theoretical and practical implications.

Effective contractor selection is crucial for successful execution of construction projects. In contrast to the conventional lowest-bid approach prevalent in the public sector, this study focuses on developing a framework that minimizes time and cost overruns by considering diverse criteria for contractor selection. A variety of machine learning models, including multi-linear regression, random forest, Support Vector Machine, and Artificial Neural Network, have been employed, with multi-linear regression proving to be the most effective, achieving the lowest Mean Squared Error of 0.00003366. To determine the final order allocation, a multi-objective mathematical model was utilized to optimize conflicting criteria, such as time and cost overruns, sustainability, risk, and safety aspects related to shortlisted contractors. The findings highlight the significance of specific selection criteria, such as turnover, experience in similar projects, qualification of staff, technology utilization, client satisfaction, accident records, available bid capacity, and socioeconomic factors. This study emphasizes a three-phase decision-making framework for contractor selection and order allocation, particularly in public construction projects, with a focus on sustainability. By adopting this approach, government agencies can enhance infrastructure projects and minimize overruns through optimization and analytical tools, which aligns with the Gati-Shakti scheme of the Indian government. It is recommended that clients embrace a holistic approach to contractor selection, considering both technical and non-technical factors, to ensure successful project outcomes.

Traditionally, informal firms are assumed to be a homogeneous mix of firms structurally different from formal firms. However, the emerging literature recognizes the high level of heterogeneity among the informal firms and hypothesizes that these informal firms vary in terms of their degree of informality. The goal of this study is to understand the characteristics of the firms operating at different levels of informality and to investigate its impact on firm performance, using a nationally representative dataset from India. We find that firms that are female-owned, rurally located, unbanked, have small asset sizes, and belong to traditional sectors are more likely to operate at higher informal levels. We also find that less informal firms are more productive. We also estimate the average treatment effect using propensity score matching as a robustness check.

PurposeThe increasing prevalence of a wide range of infectious diseases, as well as the underwhelming results of vaccination rates that may be traced back to problems with vaccine procurement and distribution, have brought to the fore the importance of vaccine supply chain (VSC) management in recent years. VSC is the cornerstone of effective vaccination; hence, it is crucial to enhance its performance, particularly in low- and middle-income countries where immunization rates are not satisfactory.Design/methodology/approachIn this paper, the authors focus on VSC performance improvement of India by proposing supply contracts under demand uncertainty. The authors propose three contracts - wholesale price (WSP), cost sharing (CS) and incentive mechanism (IM) for the government-operated immunization program of India.FindingsThe authors' findings indicate that IM is capable of coordinating the supply chain, whereas the other two contracts are inefficient for the government. To validate the model, it is applied to a real-world scenario of coronavirus disease 2019 (COVID-19) in India, and the findings show that an IM contract improves the overall efficiency of the system by 23.72%.Originality/valuePrevious studies focused mainly on the influenza VSC industry within developed nations. Nonetheless, there exists a dearth of literature pertaining to the examination of supply contracts and their feasibility for immunization programs that are administered by the government and aimed at optimizing societal benefits. The authors' findings can be beneficial to the immunization program of India to optimize their VSC cost.

PurposeThis study aims to review the computational framework of SDGs in India, so that a mid-course correction can be contemplated.Design/methodology/approachThis study deploys, inter alia, econometric analysis to probe the robustness of indicators of SDG India Index 3.0. Methodologically, the study intensively probes the robustness of SDG India index and extensively refers to the global SDG indexes for cross-checking.FindingsThough the three editions of SDGI index mark significant efforts taken towards measuring the progress of SDGs in India, the paradigm suffers from the problem of too many indicators chasing only few targets, quantitative and qualitative issues with indicators, vintage pollution, partial coverage of targets and robustness issues.Research limitations/implicationsThis study has the limitation that it could not check the robustness of SDG scores with different weights assigned to indicators and future researchers can take up that interesting assignment.Practical implicationsSince measuring the SDG progress through SDG index is a global endeavour, the findings of this study are important for almost all countries of the world, as it is still not too late to do mid-course correction because it is not the measurement that matters at the end of the day, rather it is the outcome of sustainable development that every country cares about.Social implicationsThe obfuscation of layers of SDG index in crafty, glossy and power-point-presentation-oriented SDG reports should get the reality check through such review of the computational framework of SDGs.Originality/valueThis is the first study that unpacks the layers of SDG index computation in general and comprehensively reviews the Indian SDG indexing method in particular.

Social media significantly influences travel and tourism decisions by showcasing destinations, sharing user experiences, and influencing recommendations, ultimately shaping individuals' choices and preferences. During and after the COVID-19 pandemic, social media has influenced people's travel decisions by providing real-time updates, safety guidelines, and virtual experiences, leading to changes in travel plans and preferences. However, little attention has been paid to the effect of social media on travel and tourism-related decisions. Therefore, this paper recognizes the importance of social media and uses sentiment analysis to understand the perceptions about traveling and tourism during the pandemic. We also try to find if the effect of public tweets from social media influencers differs from ordinary people. The study uses public tweets over a one-year pandemic period, assessed by splitting the dataset into two parts, namely influencer tweets and ordinary tweets, based on the number of followers. The keywords were extracted and exposed to different groups randomly to understand the effect of the Twitter. We observe that negatively worded tweets amplified negative emotions, and positive ones increased positive emotions and impacted peoples' travel-related decisions. Furthermore, it was ascertained that exposure to varied tweets related to pandemics significantly affects people's emotions in different groups.

PurposeDrawing on a framework of sustainable career theory, this paper aims to understand the interplay of agentic and contextual factors for digital micro-entrepreneurs to lead sustainable careers.Design/methodology/approachEighteen YouTube content creators in India participated in semi-structured interviews, offering coverage of digital content creators across acting, cosmetics, finance, fitness, food, law, modelling, music, teaching, travel, and video games.FindingsThe findings showed three agentic and three contextual themes associated with the career sustainability of a digital micro-entrepreneur. Additionally, four paradoxes were identified, capturing the interplay between the agentic and contextual themes.Practical implicationsThe career of a digital micro-entrepreneur is a dichotomy of promising hope, stardom, and flexibility while concealing challenges like precarity, hate comments, and financial instability. Knowing this can help individuals make better-informed career decisions.Originality/valueThe study advances sustainable career theory by capturing insights from digital micro-entrepreneurs in India to understand the interplay of agentic and contextual factors that create a series of paradoxes for such individuals to navigate over time.

The abundance of country-level socio-economic development indices is of limited help unless sub-country-level indices on the quality of policies are also available. Tracing the regional indices landscape of India, this study proposes the state-level Environment Policy Stringency Index for Indian states. Capturing Indian states' policies across six areas with weight determination done deploying principal component analysis and Data Envelopment Analysis-Benefit of Doubt approach, the composite index calculated in the study also examines the scores grouping the sub-national units based upon the income levels. Besides ranking for inter-state comparison, the proposed index is significantly associated with particulate matter pollution levels in states. This study has three key contributions: conceptualising the principal-based sub-national index while making a case for developing sub-country level policy indices, identifying state-level environment policy variables and constructing an Environment Policy Stringency Index for Indian states.

This study examines the impact of changes in consumer confidence and uncertainty related to economic policy, financial markets, and the crude oil market, on the returns and risk of the UK travel and leisure stock index. Using monthly data from November 2005 to February 2021 and applying quantile regressions and copula-based conditional value-at-risk (CoVaR) measures, the results are as follows. First, consumer confidence and uncertainties significantly impact the travel and leisure index returns across various quantiles, however, the impact is stronger at the left tail than the right tail; furthermore, the sign and magnitude of the impact differ across the various uncertainty measures. Second, there are significant upside and downside extreme risk spillovers from the extreme movements in the consumer confidence and uncertainty indices to travel and leisure index returns, with evidence of an asymmetric impact. Third, the results are influenced by the COVID-19 pandemic and global financial crisis. These findings have implications for market participants, such as portfolio managers, individual and institutional investors, and policymakers in the UK travel and leisure industry.

Purpose - This study aims to conduct an extensive bibliometric analysis of research across COVID-19 and human resource management (HRM). It captures an exhaustive conceptual understanding of theoretical foundations, research trends, developments and research directions in the HRM domain. Design/methodology/approach - A set of 505 HRM and COVID-19-specific articles collected from the Scopus database were systematically analyzed using a two-tier method. In the first tier of analysis, the evolution and current state of research are identified using citation analysis. In the second tier, network analysis and content analysis of research clusters and thematic mapping are done to identify the prominent research themes and research gaps and suggest future research directions. Findings - The study highlights the emergence of six research clusters: SHRM and competitive advantage, employer branding and employee engagement, crisis management and resilience, challenges, career shock and job demand resources and burnout. The thematic mapping categorizes the themes into four categories: motor, basic, emerging or declining, and niche research themes published on COVID-19 and HRM. To understand the socio-cultural dynamics and cross-cultural issues during human resource management, the findings emphasized the need for the increased contribution of researchers and practitioners, especially from the developing and emerging nation's context. Increased co-authorship among influential authors and institutions will also help formulate strategies and policies to effectively deal with similar pandemics. Originality/value - Unlike the previous literature review, the present findings provide meaningful insights for formulating people management techniques, policies, and practices in response to COVID-19 or similar pandemics.

Digital enabled agility reflects the transformative outset of an organisation to first upgrade its business processes digitally towards facilitating real-time information processing/capabilities. Second, tapping from real-time capabilities, digital enabled agility maximises an agile response's efficacy in enhancing the sophistication of rapidity, flexibility, and sensing involved. In this backdrop, driven by newer IT infrastructure and disruptive technology, this research accentuates on Industry 4.0 digitalisation to understand how a manufacturer can gain digital enabled agility. An empirical survey of manufacturers within the premise of Industry 4.0 is conducted. Drawn from the findings, the capabilities of traceability and visibility can be facilitated by Industry 4.0 that would improve information sharing and information quality in real-time. These capabilities are key propellants to unlock the digital extent of agility. This research however details further how this scope of agility is an extension to that of the scope of typical agility in terms of its ability to handle expansive information processing needs and dynamic coordination/resource orchestration. Insights are weaved under the purviews of (a) organisational information processing view and (b) the manufacturer who is coordinating contemporary dynamic production and allied value chain requirements.

Organizations have recently seen a significant transition from implementing technologies in business processes. The cutting-edge technology, such as artificial intelligence (AI), makes business firms more competitive in a dynamic world. This study aims to investigate key variables that drive success of AI to improve financial performance and values of a firm. The inter-relationships among variables are established to explain the emergence of AI in a novel hierarchical-model. The study deployed Total Interpretive Structural Modeling and Cross-Impact Matrix Multiplication Applied to Classification for developing a hierarchical model to analyze inter-relationships among identified key variables. The results hold important insights for strategic decisions and are useful for business firms to invest in advanced technology, such as AI, to enhance business performance and revenue in domestic as well as in global markets. Insights drawn from analysis will help business firms to grow in a competitive landscape. The decision makers can utilize the proposed hierarchical-model to enhance the performance of business along with process automation. The found interactions amongthe key variables can be utilized to understand the ecosystem that drives business performance.

In recent years, several probability distributions have been introduced in the literature to analyze the data exhibiting an upside-down bathtub-shaped failure rate; an inverse Pareto distribution (IPD) is an appropriate choice among them. For stress-strength reliability models, estimation of parameters is an interesting area of research. In this article, we estimate the stress-strength reliability parameter R=P(X>Y) (where X and Y are strength and stress variables, respectively) of the IPD, whereby we focus on the problem of fixed-accuracy confidence interval estimation of R. It is established that the proposed interval estimation problem cannot be solved with the help of any fixed sample technique. As a result, we propose a two-stage sequential sampling strategy (which reduces the sample size significantly) to solve the given estimation problem. We obtain the expressions of several exact operating characteristics associated with our two-stage sampling technique. We also establish that the proposed two-stage procedure enjoys interesting first-order asymptotic properties. The detailed simulation analyses support our theoretical findings, and two real data sets based on insurance claims reinforce the practical utility of the proposed technique.

The paradigm shift brought about by gig work, marked by its flexible and non-traditional employment structures, necessitates a comprehensive understanding of its intricate interaction with Human Resource Management (HRM). Through a systematic literature review, this study endeavors to synthesize the existing body of knowledge, illuminating the evolving role of HRM within the dynamic landscape of contemporary gig work. Drawing from an extensive array of scholarly articles, this study reveals that HRM is undeniably pertinent in gig work. However, its application necessitates an innovative and tailored approach that diverges from traditional employment paradigms. The literature encompassing the interface of HRM and Gig work is distilled into three overarching themes: emanant relevance, refurbished relevance, and obsolete relevance. These thematic classifications reflect the dynamism and evolution of HRM practices as they intersect with gig work. In its culmination, this review accentuates the far-reaching implications of its findings for both academic discourse and practical implementation. The synthesized insights contribute substantively to advancing scholarly comprehension of gig work's intertwined relationship with HRM, thus serving as a guidepost for future research endeavors.

In the context of rapid urbanization and urban sprawl, growing concerns about sustainability in urban governance have come to the forefront. The study employed exploratory bibliometric analysis to examine the literature on sustainable urban governance and critically investigate how sustainability is complexly woven into urban governance as a multidimensional phenomenon. The paper addresses the existing literature gaps, including contextual challenges and inadequate theoretical-methodological underpinnings, by analyzing 2,194 scholarly outputs. We propose a sustainable urban governance framework that rationalizes contextual justifications (at the macro-meso-micro and interlevel) by synthesizing the concept of good urban governance, interlinks of sustainability dimensions, and multilevel governance systems. Sustainable urban governance is defined in this study as a process and system that creates harmonious coexistence among urban settings' ecological and social strata through integrating rationalized contextual justifications, collective sustainability objectives, and inclusive urban resilience plans.

PurposeThis research aims to examine how an exhibitor manages its relationship with visitors in trade fairs to achieve desired outcomes. Drawing on the relational (group-value) model of justice, this research argues that visitors' procedural and distributive fairness perceptions impact their happiness, relationship commitment, and behavioral intentions with exhibitors.MethodologyData comprising 350 business visitors from eight trade fairs related to the electronics, telecommunications, automobiles, apparel, and renewable energy industries were analyzed.FindingsThe findings show that while procedural fairness perceptions significantly impact visitors' happiness, distributive fairness perceptions do not have a significant relationship. Happiness leads to a positive relationship between visitors' commitment and behavioral outcomes.Originality/Value/ContributionThis research is one of the earliest attempts to evaluate the role of fairness perceptions and happiness in the context of trade fairs. The results also indicate that small-scale visitors show less concern for procedural fairness than large-scale visitors, but they show a higher tendency for relationship commitment and behavioral intentions than large-scale visitors.

This study examines internal greener operations in Indian healthcare during COVID-19 pandemic. Specifically, the research explores the interrelationships among three parallel healthcare lines: general care, emergency care, and biomedical waste (BMW) management to fulfill greener healthcare's targeted sustainable development goals. We use the three parallel stage data envelopment analysis (DEA) approach model to assess efficiencies of the overall system and the individual parallel stages. We collected panel data for cities in the state of Maharashtra, India during the second wave of pandemic in 2021. We find that the effectiveness of general and emergency medical services depends on the requirements of healthcare resources such as beds and equipment in times of pandemics. By contrast, the capacity of individual BMW treatment processes such as incineration, autoclave, shredder, and deep burial would have a bearing on the efficiency of both BMW management and the total system for greener operations. In the second phase, we evaluated the impact of context-specific exogenous factors using a regression model. We found that literacy level was the most important factor at all three parallel stages separately. Additionally, the total population and number of female vaccinated persons were significant across the system while population density and number of male vaccinated persons were inconsequential factors. Interestingly, the Wilcoxon rank-sum hypothesis test offered no evidence to suggest that performance of general care and BMW management, and emergency care and BMW management were equivalent. Implications of these findings for academic theory, practitioners, and policy makers are offered.

PurposeEmpirical attempts to recommend enabling mechanisms for organizational unlearning are sparse and have almost neglected the vital role of leadership in transforming organizations through unlearning. Based on the tenets of persistence theories like path-dependence and imprinting theory, this study examines the relationship between transformational leadership and unlearning with the mediating role of knowledge sharing, transparent internal communication and intrapreneurship.Design/methodology/approachTo analyze the hypothesized relationship between these constructs, data were collected from 452 faculty members working in Centrally Funded Technical Institutions (CFTIs) in India. The data were analyzed using Process macro (Hayes, 2022).FindingsThe results show a significant effect of transformational leadership on organizational unlearning. This effect is mediated by transparent internal communication and intrapreneurship. However, knowledge sharing did not mediate the relationship between transformational leadership and organizational unlearning.Practical implicationsThe Fourth Industrial Revolution, Covid-19, the rise of generative artificial intelligence tools like ChatGPT and policy reforms have pushed higher educational institutions to transform by unlearning old practices and experimenting with new ones. This paper informs how educational institutions can initiate and sustain the unlearning process.Originality/valuePersistence theories like path-dependence and imprinting theory suggest that organizations often stick with proven success formulas and find it challenging to adopt new practices. Moreover, path dependence theorists advocate the role of an external intervening mechanism to break away from rigid and inefficient routines (or paths). This paper argues that in addition to external events (e.g. crisis, etc.), transformational leaders combined with organizational processes also help in unlearning obsolete knowledge and routines.

Purpose Waste management is a crucial aspect of sustainable development, but is it economically sustainable for marginalized informal firms? The study tries to answer this question by revisiting the Porter-Wagner dilemma about the association between environmental management (EM) and firm performance (FP). The study looks into the various liquid waste management practices (LWMPs) adopted by them and the overall impact of LWMPs on firms' economic performance.Design/methodology/approach The study uses the latest available cross-sectional data source on Indian informal firms by the National Sample Survey Office (NSSO), 73rd survey round 2015-16. First, ordered logistic regression was used to analyse the factors that impact a firm's adoption of a particular LWMP. Subsequently, to capture the heterogeneity among the firms based on productivity and size, a quantile regression (QR) was employed to analyse the impact of LWMPs on firm productivity. Additionally, the propensity score matching technique was used to address endogeneity concerns.Findings The authors find that bigger, urban-located and female-owned firms adopt cleaner LWMPs that positively impact their economic performance. Furthermore, the QR analysis observed that the most productive firms could extract higher returns from adopting cleaner LWMPs, indicating the relevance of the Porter-Wagner dilemma, i.e. environmental and economic sustainability are possibly symbiotic, thus having a feedback mechanism.Originality/value To the authors' limited knowledge, this is the first study analysing the relationship between EM and FP among the informal sector firms, which are away from any regulations or obligations. Since sustainability is a two-way process, policies should be devised that incentivise sustainable business practices.