Search results

The objective of this paper is to synthesise the published literature on consumer awareness and acceptance of Sustainable Fashion (SF) and highlight that sustainability decisions taken across procurement, designing, manufacturing and retailing must include the consumer perspective of SF.

Systematic Literature Review (SLR) on sustainable fashion combined with consumer behavior was conducted. The study approach involved descriptive analysis, content analysis and theoretical analysis in the first section. The later sections focus on sustainability practices across the apparel supply chain that can foster acceptance of sustainable fashion.

In this review paper, five solutions that are typically used for leveraging consumer awareness and acceptance towards sustainable fashion are identified from the latest research papers: (1) attention to micro-sensitive factors (2) shared responsibilities (3) repositioning sustainable fashion for larger audience (4) positioning conscious fashion and (5) unified approach. These solutions are proposed as most important for achieving success in sustainable production and sustainable consumption (SPSC) for the fashion industry. Further, suggestions for how to embed sustainability related business decisions across sourcing, designing, manufacturing, distribution and recollection and retailing are also provided.

Through this research, a clear view emerges of the progression of publication and where future research should be directed to popularise sustainable fashion among consumers. Research findings and proposed solutions will be valuable inputs for brand managers, marketers and retailers as they conceive new plans and make decisions about addressing sustainability challenges in textile and apparel manufacturing firms.

This is a first of its kind of study on sustainable fashion that highlights the importance of understanding consumer behaviour in influencing sustainability decisions required across sourcing, designing, manufacturing and retailing to achieve substantial economic advantages in the fashion industry. End-to-end supply chain processes (i.e. procurement, design, manufacturing, marketing and retailing) are considered to identify several factors that influence consumer behavior in favor of sustainable fashion throughout the supply chain.

International trade is a long-standing issue for the development of any country. In the traditional theory of trade exports or trade pattern arises because of supply side differences between countries such as technological or factor endowment differences. Such theories predict inter-industry trade but not intra-industry trade (IIT). But in contrary, the simultaneous export and import of products of the same sector was led after the industrialization of developed countries from the 1960s onwards, which was described as “IIT” by [Balassa, B. (1986). Oxford Economic Papers, 38, 220–233]. In this study, India's bilateral IIT with major Asian trading partners was analyzed and the trends in IIT level for horizontal and vertical IIT were observed separately, along with gravity model for the year 2009–2018. This study examined the geographic component in knowledge flows, which could be found at the international level and whether or not an exchange of knowledge is related to foreign trade, particularly IIT. To measure the IIT level for investigating trade patterns between India and member countries of major Asian trading partners, IIT index will be used, known as Grubel-Lloyd index.

The study examined a wide range of proactive supply chain practices to demonstrate a cross-linkage among them and to understand their effects on both practitioners of previous decision-making models, frameworks, strategies and policies. Here, six supply chain practices are empirically evaluated based on 28 constructs to investigate a comprehensive model and confirm the connections for achieving performance and competence. The study presents a conceptual model and examines the influence of many crucial factors, i.e. supply chain collaboration, knowledge, information sharing, green human resources (GHR) management and lean-green (LG) practices on supply chain performance.

Structural equation modeling (SEM) examines the conceptual model and allied relationship. A sample of 175 respondents' data was collected to test the hypothesized relations. A resource based view (RBV) was adopted, and the questionnaires-based survey was conducted on the Indian supply chain professionals to explore the effect of LG and green human resource management (GHRM) practices on supply chain performance.

The study presented five constructs for supply chain capabilities (SCCA), five constructs for supply chain collaboration and integration (SCIN), four constructs for supply chain knowledge and information sharing (SCKI), five constructs for GHR, five constructs for LG practices (LGPR) and four constructs for lean-green SCM (LG-SCM) firm performance to be utilized for validation by the specific industry, company size and operational boundaries for attaining sustainability. The outcome emphasizes that SCCA positively influence GHRM, LG practices and LG supply chain firm performance. However, LG practices do not influence LG-SCM firm performance, particularly in India.

The study exploited multiple practices in a conceptual model to provide a widespread understanding of decision-making to assist in developing a holistic approach based on different practices for attaining organizational sustainability. The study stimulates the cross-pollination of ideas between many supply chain practices to better understand SCCA, SCIN, SCKI, GHRM and LG-SCM under a single roof for retaining organization performance.

This study aims to examine the impact of the stringency of COVID-19 protocols on the volatility of sectoral indices during the period 03:2020–05:2021. Specifically, this study investigates the role of economic disturbances on sectoral volatility by applying a range of conditional volatility techniques.

For this analysis, two approaches were adopted. The first approach considers COVID stringency as a factor in the conditional variance equation of sectoral indices. In contrast, the second approach considers the stringency indicator as a possible determinant of their estimated conditional volatility.

Results show that the stringency of the protocols throughout the pandemic phase led to an instantaneous spike followed by a gradual decrease in estimated volatility of all the sectoral indices except pharma and health care. Specific sectors such as bank, FMCG, consumer durables, financial services, IT, media and private banks respond to protocols expeditiously compared to other sectors.

The key contribution of this study to the existing literature is the innovative approach. The inclusion of the COVID stringency index as a regressor in the variance equation of the conditional volatility techniques was a distinctive approach for assessing the volatility dynamics with the stringency of COVID protocols. Furthermore, this study also adopts an alternative approach that estimates the conditional volatility of the indices and then tests the effect of the stringencies on estimated volatility in a regression framework.

The study examines how the liquid assets holdings among non-financial Indian firms vary due to tightening monetary policy and increasing macroeconomic uncertainty.

The authors analyze 5,640 firms for the period 2011–2021. The authors first estimate India’s monetary policy shocks by decomposing the exogenous shocks from the systematic component of monetary policy changes. The authors then examine the effects of the estimated monetary policy shocks and a range of macroeconomic and policy uncertainty indicators on companies’ cash and bank balances to asset ratios using two-step system generalized method of moments (GMM) estimators.

The authors find that monetary policy shocks cause the cross-sectional variances for the firms’ liquidity holdings to increase. In anticipation of macroeconomic volatility, companies respond to these shocks after taking into account all the firm-level information to minimize the opportunity costs of holding extra cash or too few cash balances that can hamper firms’ operations. Furthermore, compared to other shocks, the contribution of inflation-induced shocks is predicted to be the largest in the cross-sectional deviation of the firm’s cash holdings. The authors also find that low-growth, older and financially constrained firms observe lesser heterogeneity in their cash holdings as they tend to hold cash as a precautionary buffer.

The authors’ approach to the analysis is unique in many ways. To address potential transmission bias, the authors use nowcasts and forecasts of real gross domestic product (GDP) growth and inflation to generate a series of exogenous monetary policy shocks for identifying unanticipated changes in short-term interest rates. Subsequently, the authors estimate how these shocks affect the cross-sectional deviation of liquid assets. For estimating the effects of macroeconomic uncertainty on corporate cash demand, the authors utilize a range of proxies for uncertainty. Unlike previous attempts, the authors offer evidence for a developing and fast-emerging economy.

In India, artificial intelligence (AI) application in supply chain management (SCM) is still in a stage of infancy. Therefore, this article aims to study the factors affecting artificial intelligence adoption and validate AI’s influence on supply chain risk mitigation (SCRM).

This study explores the effect of factors based on the technology, organization and environment (TOE) framework and three other factors, including supply chain integration (SCI), information sharing (IS) and process factors (PF) on AI adoption. Data for the survey were collected from 297 respondents from Indian agro-industries, and structural equation modeling (SEM) was used for testing the proposed hypotheses.

This study’s findings show that process factors, information sharing, and supply chain integration (SCI) play an essential role in influencing AI adoption, and AI positively influences SCRM. The technological, organizational and environmental factors have a nonsignificant negative relation with artificial intelligence.

This study provides an insight to researchers, academicians, policymakers, innovative project handlers, technology service providers, and managers to better understand the role of AI adoption and the importance of AI in mitigating supply chain risks caused by disruptions like the COVID-19 pandemic.

This chapter looks at the experiments of the Aam Aadmi Party led government’s initiatives in building teacher quality for its government schools in the capital city. Outlining the contours of neoliberal influence on Indian education policy and its consequences on teacher quality, the chapter explores the political rationality that governs the case of Delhi. It does this by understanding the changing subjectivities of the school teachers within the educational reforms. The government schools in Delhi have been blamed for worsening school performance especially in student learning outcomes through basic educational tests conducted by various assessment and evaluation surveys. Among other reasons, poor teacher quality has been identified as one of the major causes of this poor performance of government school children. Therefore, gaps were identified in the teacher support system and efforts were made to revamp the system. The chapter brings out in detail how the state’s initiatives in educational reforms have produced paradoxical situations and unintended effects in practice as the state has retained a controlling role even though the reform strategies show a shift toward increasing autonomy and deregulation.

The purpose of this paper is to identify and model critical barriers to cloud computing adoption (CCA) in Indian MSMEs by the interpretive structural modeling (ISM) approach.

In this paper, through a literature survey and expert opinions, 14 critical barriers were identified, and the ISM tool was used to establish interrelationship among the identified barriers and to determine the key barriers having high driving power.

After analyzing the barriers, it was found that three barriers, namely, lack of confidentiality (B8), lack of top management support (B3) and lack of sharing and collaboration (B2) were most significant.

The developed model is based on the expert opinions, which may be biased, influencing the final output of the structural model. The research implications of the developed model are to help managers of the organization in the understanding significance of the barriers and to prioritize or eliminate the same for the effective CCA.

This study is for the first time an attempt that has been made to apply the ISM methodology to explore the interdependencies among the critical barriers for Indian MSMEs. This paper will guide the managers at various levels of an organization for effective implementation of the cloud computing practices.

In the last 10 years, India has amended its laws dealing with sexual offences against women with the changes ranging from increasing terms of imprisonment for the offence of rape to state-funded compensation schemes for women and child victims. In this regard, challenges persist for the agencies of the criminal justice system in India especially the courts to realise the vision of restorative justice as these forums have to navigate the relevant statutory provisions and binding precedents. This chapter seeks to analyse the challenges faced by courts in proper reintegration of victims and offenders of sexual offences, the institutional responses of the courts and suggests reforms to the criminal justice system in India in consonance with the principles of restorative justice acknowledged in the restorative justice movement in the international discourse.