Traditional linear models struggle to capture the intricate relationship between dynamic container throughput and its complex interplay with economic fluctuations. This study introduces a novel, deep learning-based multivariate framework for precision in demanding landscapes. The framework consistently outperforms eight established benchmark models by employing vital economic indicators like GDP and port tonnage, identified through rigorous predictor importance analysis of an initial set of four variables, including imports and exports. Statistical significance is demonstrably achieved through the Diebold-Mariano and Wilcoxon rank-sum tests. Utilizing the Port of Singapore as a case study, the framework offers agile adaptability for the ever-evolving global supply chain. Comprehensive analyses ensure robustness, decoding intricate throughput dynamics. Incorporating noise-assisted multivariate empirical mode decomposition (NA-MEMD) for nonlinear decomposition and bidirectional long short-term memory (BiLSTM) for time series dependencies, this innovative approach holds promise for revolutionizing container throughput forecasting and enhancing competitiveness in the global market through optimized resource allocation and streamlined operations.

Purpose This study aims to systematically review various behavioral biases that impact an investor's decision-making process. The prime objective of this paper is to thematically explore the behavioral bias literature and propose a comprehensive framework that can elucidate a more reasonable explanation of changes in financial markets and investors' behavior.Design/methodology/approach Systematic literature review (SLR) methodology is applied to a portfolio of 71 peer-reviewed articles collected from different electronic databases between 2007 and 2021. Content analysis of the extant literature is performed to identify the research themes and existing gaps in the literature.Findings This research identifies publication trends of the behavioral biases literature and uncovers 24 different biases that impact individual investors' decision-making. Through thematic analysis, an attribute-consequence-impact framework is proposed that explains different biases leading to individual investors' irrationality. The study further proposes directions for future research by applying the theory-characteristics-context-methodology framework.Research limitations/implications The results of this research will help scholars and practitioners in understanding the existence of various behavioral biases and assist them in identifying potential strategies which can evade the negative effects of these biases. The findings will further help the financial service providers to understand these biases and improve the landscape of financial services.Originality/value The essence of the current paper is the application of the SLR method on 24 biases in the area of behavioral finance. To the best of the authors' knowledge, this study is the first attempt of its kind which provides a methodical and comprehensive compilation of both cognitive and emotional behavioral biases that affect the individual investor's decision-making.

Traditionally regarded as one of the least digitised industries, agriculture is now transforming due to the emergence of digital platforms and ecosystems. Extant literature underscores Agtech platforms as business solutions capable of remedying operational inefficiencies, diminishing transaction costs, enhancing information exchange, mitigating spatiotemporal disparities, facilitating market integration, and generating novel forms of value. Nevertheless, persistent ambiguity surrounds the identification and assessment of the functional roles of peripheral actors, referred to as complementors, who play a pivotal role in engendering network effects. Grounded in network externality theory and platform value proposition framework, this study seeks to comprehensively discern complementors, lead firms, and end-users associated with Agtech platforms and their overarching value propositions. Employing the case research method, we synthesise existing literature and review archival sources while focusing on four illustrative cases: Dehaat, Agrielevate, IFFCO Bazar, and KRIBHCO-CSC-eGov. The analysis was further strengthened through consultation with domain experts, facilitating triangulation and validation. This study offers insights into complementor-core, lead firm, and end-user groups within Agtech platforms, thus deepening our epistemic comprehension.

PurposeThe purpose of this study is to analyse the impact of corporate attributes like a company's profitability, size, age, leverage and board size on companies' sustainability reporting as measured through India's new business responsibility and sustainability reporting (BRSR) framework.Design/methodology/approachA random sample of 130 companies was taken from the top 1,000 listed companies on the National Stock Exchange. Sequential mixed methods research approach was used to prepare a sustainability quality index. Then, a hierarchical multiple regression analysis was performed to examine the impact on the quality of reporting by Indian companies.FindingsInterestingly, the analysis revealed that traditional metrics like age, profitability, board size and leverage did not have significant associations with reporting quality. Rather, the size of a company in terms of market capitalisation was found to have a strong positive impact on sustainability reporting.Research limitations/implicationsThis was a cross-sectional study, as time series data for BRSR reporting is not yet available. Also, only five parameters were taken for analysis. Lastly, subjective judgment in content analysis may be involved.Practical implicationsThis suggests that only larger companies in India are prioritising sustainability reporting over smaller ones. It affirms the legitimacy and stakeholder theory in the Indian context.Originality/valueTo the best of the authors' knowledge, this study is one of the first endeavours to assess the efficacy of the new Indian BRSR framework and test its primary objectives. Furthermore, significant implications have been given for managers to catalyse and reinforce the sustainability momentum down the lane across companies of all sizes in India.

The environmental impact of the transport sector has a significant contribution in the carbon emissions. To reduce fossil fuel consumption and promote clean fuel, many countries are considering hydrogen as an alternative fuel and a bridge to sustainable development and achieve net zero target. Indian government has taken multiple policy initiatives to promote hydrogen fuel adoption in India. But nevertheless, the major presence of the multiple barriers limits the mass adoption of hydrogen as a preferred fuel. Therefore, identification and assessment of the key internal and external barriers of the hydrogen fuel vehicles adoption is required to mitigate the climate change issues. This study has identified and analyzed the barriers. The criticality assessment of the barriers is done by fuzzy based hybrid approach analytic hierarchy process. Later, sensitivity experiments are conducted to verify the robustness of the model. The findings of the study show that technical barriers are most critical barriers in the adoption of hydrogen fuel vehicles in India. The result of the study also indicates that India would require to build the hydrogen supply network and infrastructure, improve consumer awareness, favourable policies and develop efficient production technology for the mass adoption of hydrogen as a fuel.

In recent years, food loss and waste (FLW) have become an essential issue at the top of the international community's agenda. Since more people are afflicted by this problem every day, the global population would be forced into poverty and starvation without finding an immediate solution. Therefore, in order to decrease FLW, well-designed and sustainable food and cold supply chains (FCSCs) are needed. Additionally, refrigerated transportation systems can be crucial in developing sustainable supply chains. According to some empirical research, the technological capabilities of reefer vehicles or trailers differ significantly. Thus, selecting the reefer vehicle is a complex decision-making problem and selecting appropriate reefer vehicles may have a critical role in constructing successful supply chain systems and reducing food waste and loss. The current research proposes an efficient, robust and practical decision-making framework that can overcome uncertainties to tackle this decision-making problem. The managerial and strategic implications of the study also aid in decreasing FLW and restructuring FSC for industrial context and support to the UN's sustainable development goals (SDGs). Later, an exhaustive sensitivity analysis was conducted to examine the developed model's validity and application, confirming the model's robustness and dependability.

PurposeThis study aims to assess the efficiency of managing working capital in 1,388 Indian manufacturing firms from 2008 to 2019 and investigate the effects of firm-specific and macro-level determinants on working capital management (WCM) efficiency.Design/methodology/approachThe current study accommodates a slack-based measure (SBM) in data envelopment analysis (DEA) for computing WCM efficiency. Further, we implement a panel data fixed-effects model that controls for heterogeneity across firms in determining the relationships of selected variables with WCM efficiency.FindingsThe results highlight that manufacturing firms operate at around 50 percent efficiency, which is constant throughout the study period. Furthermore, among the selected variables, yield, earnings, age, size, ability to create internal resources, interest rate and gross domestic product (GDP) significantly affect WCM efficiency.Originality/valueInstead of the traditional models used for assessing efficiency, the SBM-DEA model is unit-invariant and monotone for slacks, implying that it can handle zero and negative data, which overcomes the incapability of prior DEA models. Hence, this provides accurate efficiency scores for robust analysis. Additionally, this paper provides a holistic working capital model recognizing firm-specific and macro-level determinants for a more explicit estimation of the relationship between WCM efficiency and the selected determinants.

This paper explores the effects of innovational investments in information technology (IT) on the productivity performance of firms. We employ a micro-level dataset of 3582 firms from Indian manufacturing spanning 1998 to 2016 to identify some critical channels through which IT investments may impact productivity. We find a significant impact of inter-industry network spillovers, suggesting that the convenience drawn from IT assets transmits to firms in other sectors of the economy without the recipient firms paying for it. These spillovers are higher for firms in the top 50 percentile of the industry in terms of their IT assets. Our results also show strong complementarities between IT, R&D, and disembodied technology purchased by the firm. We find that these technological inputs offer a synergistic effect on productivity. Our results also highlighted that these synergies vary by ownership and export status. IT also seems to mitigate the diminishing gains to R&D as firms scale their R&D effort. Overall, we show that IT investments not only provide crucial productivity returns but also synergize other technological investments to produce superior overall gains.

Several developing economies have been generating fast growth, but formal employment generation remains a concern, causing a significant workforce to continue working in the informal sector. In this context, this study investigates the employment effects of international trade and in-house R&D in the Indian case. Our attempt is important because India is not only the largest country in terms of population but also the largest working population in the world. We coalesce industry-level data from two different sources for the period 1991-2018 and employ a powerful system GMM estimator in the analysis. Our findings are interesting and vital. We show that although the role of trade is overall positive, export and import have contrasting roles individually in generating employment. Most generally, exporting is a generator of employment, while importing causes a loss in it. Our analysis implies that the interplay of trade, and individually that of exports and imports, with in-house R&D depends on many factors and may be more intricate than previously assumed.

PurposeThis study aims to examine the role of economic political uncertainty (EPU) on various corporate policies, namely, cash reserves, investment, capital structure and operating activities of Indian listed firms.Design/methodology/approachTo assess the influence of policy-related uncertainties, the author uses the India-specific EPU news-based index constructed by Baker et al. (2016) as a proxy for policy uncertainties. This study uses data from listed Indian firms spanning the period 2003 to 2019. The author uses panel regression models with firm-fixed effects to analyze the impact of EPU on corporate policies, including cash reserves, leverage and CAPEX, while considering key control variables.FindingsIn response to heightened EPU, firms tend to increase their cash reserves, curtail their investment activities and favour secured financing options. Notably, this study aligns with the real options framework, demonstrating that firms with substantial investment irreversibility significantly reduce their capital expenditures during periods of elevated EPU. Additionally, the results reveal that rising EPU corresponds to heightened borrowing costs and increased operating expenses for firms.Originality/valueIn contrast to prior research that predominantly investigated the impact of EPU on the decisions of listed firms in developed markets, this study delves into the role of EPU on corporate policies among listed firms in India. This focus is particularly relevant, given the significant policy changes that have transpired in the Indian business landscape in recent years.

One of the most pernicious and pervasive threats to the integrity of governments, economies, and societies worldwide is the insidious and corrosive influence of corruption. E-government, everywhere, is expected to play a pivotal role in combating corruption. Nevertheless, academic research has yielded varying outcomes. To address the inherent variability, this study employed data from 188 countries to thoroughly investigate the impact of e-government on corruption. Using a path modeling approach and following New Institutional Theory, this study examined the association between the two. We found an inconsistent relationship between e-government and corruption, primarily owing to a nonlinear association between the two and an omitted mediator variable of an institutional nature. Further, accountability, a social instrument, mediates this relationship. Our study offers a fresh perspective on the relationship between e-government and corruption by establishing the crucial role of accountability in the context of corruption.

This paper investigates the effect of ESG (environmental, social, and governance) disclosure scores on the firm's performance (operational, financial, and market) using Indian firms. The study assesses the critical COVID period and provides empirical evidence from the world's 5th largest economy. The findings from empirical results declare that all components of ESG are not significantly related to firm performance. We conclude that the impact of ESG-related activities is yet to be witnessed tangibly for firm performance. The study also opens an array of future research opportunities.

Purpose - Organizations widely adopt knowledge management (KM) to develop and promote technologies and improve business effectiveness. Analytics can aid in KM, further augmenting company performance and decision-making. There has been significant research in the domain of analytics in KM in the past decade. Therefore, this paper aims to examine the current body of literature on the adoption of analytics in KM by offering prominent themes and laying out a research path for future research endeavors in the field of KM analytics.Design/methodology/approach - A comprehensive analysis was conducted on a collection of 123 articles sourced from the Scopus database. The research has used a Latent Dirichlet Allocation methodology for topic modeling and content analysis to discover prominent themes in the literature.Findings - The KM analytics literature is categorized into three clusters of research - KM analytics for optimizing business processes, KM analytics in the industrial context and KM analytics and social media.Originality/value - Systematizing the literature on KM and analytics has received very minimal attention. The KM analytics view has been examined using complementary topic modeling techniques, including machine-based algorithms, to enable a more reliable, systematic, thorough and objective mapping of this developing field of research.

PurposeThis paper aims to explore the evolving needs of Indian men and their aspirations regarding work-life balance practices. The ultimate aim is to assess whether the available policies are helpful and to explore the various roadblocks in their implementation.Design/methodology/approachThis study takes a qualitative approach and draws on the semi-structured interviews of Indian men (N = 19).FindingsThe analysis revealed an asymmetrical approach of organizations toward implementing employee benefit policies. The organizations remain plagued by the notion that benefits policies are needed only by women to carry out additional family responsibilities, whereas men remain aloof from such responsibilities, which takes its strength from the patriarchal roots of Indian society. This study reveals two major themes: lack of appreciation for gender egalitarianism arising among men at the work-family interface' and the coping practices by men to address their 'role strain arising due to work-family conflict. It is noted that there is a need to formulate policies and practices to cater to men's evolving aspirations toward the family-work interface.Originality/valueThis study furthers the debate on inclusive policies for employees and examines the subsection of men for their evolving needs and aspirations. Although organizations live in the glory of having employee-friendly policies, they offer little help in advancing gender neutrality in the workplace. The inclusive policies shall also be helpful for females because it would increase the availability of their partners/spouses to share the family responsibilities.

Currently, there are limited mechanisms to control harmful greenhouse gas emissions. There is a need to contain these emissions at the source level; understanding the root cause is imperative. This would aid in monitoring and curbing those factors to minimize these harmful emissions and control incidences of energy risk. While there are studies evidencing the role of generic indicators like per capita carbon consumption on greenhouse gas levels, these are also equally influenced by climatic risk factors such as surface temperature. Research suggests that climatic factors significantly impact fluctuating greenhouse gas emissions. However, existing studies have not quantified the precise extent to which these factors drive harmful emissions, which, in turn, also curb energy efficiency and increase the costs of generation of energy alternatives. To address this gap, the outcome variable 'Total greenhouse gas emissions including land-use change and forestry' is examined using advanced machine learning algorithms such as Random Forest, Multi-layer perceptron models and Deep Neural Networks. Algorithms are chosen in the hierarchical order of accuracy to capture the differential capabilities of detecting the causation factors of harmful emissions. While the above algorithms see the essential features in terms of absolute value, there is a need to examine how each factor contributes to the emissions relative to the others. The Shapley framework of Explainable AI is therefore employed to scientifically assess the influence of different factors on consumption levels. The outcomes of the Shapley analysis are then validated through regression and further supported by the Fuzzy Analytical Hierarchy Process (AHP). The research also proposes adopting association rule mining to analyze the co-occurrence of specific climatic conditions on energy consumption. The findings of this study offer valuable insights for both society and experts in climate and energy, enabling them to develop specific strategies and targeted climatic policies for effective energy risk management. This would present an opportunity for economic transformation, job creation, technological advancement, and improved environmental and public health outcomes. While initial costs and challenges may be associated with a transition, the long-term benefits would help attain sustainable energy economics.

Contemporary careers have paved the way for protean careerists. As protean careerists, freelancers are viewed as a new breed of workforce who build their careers independent of any organisational affiliation and thus, hold full responsibility for managing and developing their own career. In this paper, we theoretically elucidate the relationship between the freelancer's career meta-competencies, perceived employability and career success. We propose a conceptual model of these relationships, along with deciphering the moderating role of occupational embeddedness and individual career stage. Our paper builds on the new career theories through offering a more holistic model of career success for freelancers that showcases the relevance of career identity and adaptability as significant for both subjective and objective career success. The paper also highlights several practical implications for freelancers that act as a guide for their survival and advancement in their protean career path.

Purpose - This study systematically reviews the existing literature on the application of gamification in logistics and supply chain management (LSCM). This study aims to categorise the literature in various logistics and supply chain domains, to conceptualise the gamification framework pertinent in the context of LSCM and to provide a research agenda for scholars in the area. Design/methodology/approach - The study's methodology adopts the Preferred Reporting Items for Systematic Review and Meta-Analysis framework to conduct a systematic literature review. Forty relevant papers published from 2012 to 2023 are included in the analysis. Findings - Augmented reality, blockchain, education, sustainability and warehousing have been identified as the key focus areas in which gamification is applied. Furthermore, the paper highlights different research approaches used to study these domains, maps the literature with gamification constructs (affordances, psychological outcomes and behavioural outcomes) and provides potential research avenues for future scholars. Research limitations/implications - This review offers evidence of the impact of gamification on workforce dynamics, employee motivation, job satisfaction, trust, employee engagement and productivity. The study significantly contributes to the academic community by offering a conceptual framework and meaningful avenues for future researchers. Originality/value - This research work contributes to the gamification, logistics and supply chain literature by providing a more comprehensive and methodical knowledge of the field. This study adds to the body of knowledge by offering a reference framework for future scholars based on a synthesis of the studies published so far in the area.

This study examines how the causal patterns of consumers' engagement and experts' external engagement are associated with their online evaluation of movies. To this end, this study identifies the interplay of two dimensions (personal and interactive engagement) of consumers' engagement and external engagement in their evaluation of movies and offers four propositions. This study utilizes fuzzy-set qualitative comparative analysis (fsQCA) on an original dataset of 264 movies released during 2018-2021 to test these propositions. Findings indicate seven configurations of consumers' engagement behavior and external engagement that explain high movie ratings. This study presents fresh insights into how two dimensions of consumer engagement behavior and external engagement combine to explain movie ratings better. The findings accentuate the importance of synergies between dimensions of consumer engagement behavior and external engagement in driving the evaluation of movies.

Purpose - The purpose of this paper is to integrate academic research on hubristic organizational leaders by proposing a comprehensive conceptual framework and research directions on the hubristic literature. Design/methodology/approach - The paper systematically reviewed 25 years of literature on hubristic organizational leaders based on the PRISMA methodology. Findings - The literature on hubristic leaders is analyzed, and a conceptual framework is presented that highlights the antecedent, consequence, mediators and moderators. Literature has primarily focused on the negative impact of hubris leadership concerning firm performance and destructive behaviors. Few scholars have explored the positive side of hubris leadership, relating it to innovation and product success. Originality/value - This paper presents the first systematic review of hubristic organizational leaders, to the best of the authors' knowledge. The review provides an improved grasp of the current status of research, trends and potential future research directions.

This study aimed to examine factors influencing the adoption of fitness wearable technologies (FWTs) by extending the Unified Theory of Acceptance and Use of Technology (UTAUT2). A survey was conducted with 574 fitness wearable users in India to test a conceptual Fitness Wearable Adoption Model (FWAM) incorporating additional constructs of obsolescence risk, health belief, and perceived accuracy alongside UTAUT2 variables. Structural equation modeling revealed performance expectancy, effort expectancy, social influence, hedonic motivation, price value, health belief, and obsolescence risk positively affected adoption intentions, while perceived security had no effect. Perceived accuracy mediated the impact of performance expectancy, while price value mediated the relationship between obsolescence risk and intentions. The research makes key contributions by adapting UTAUT2 to a new context, integrating additional adoption factors, identifying mediating mechanisms, and revealing moderating effects of age. Findings provide valuable insights into consumer acceptance of fitness wearables that can inform strategies for manufacturers, marketers, and health practitioners to promote adoption. A major focus of the investigation is to develop strategies for increasing the adoption of wrist-worn fitness technology that provides an opportunity for fitness wearable technology manufacturers to strengthen relationships with older age groups through effective communication techniques.