Search results

Body positivity movement empowered plus-size women globally to speak up boldly about their clothing needs. Retailers cannot satisfy this group with some classic style offerings anymore. By taking clue from existing literature, this study aims to identify clothing preferences and problems related to ready-made plus-size clothing in India. Although many past literature pointed out about poorly fitted and size unavailability issues worldwide, very few of them addressed about clothing style preferences.

A self-administered close-ended questionnaire was used to answer a set of objectives. A pilot study with 40 plus-size women was carried out to check the reliability and validity of the instrument. Four hundred subject's data were gathered from six Indian cities with a purpose of varied geographical importance. Statistical tests like binomial distribution was used to analyze fit-related problems of 12 bodily sites such as shoulder, upper arm, lower arm, bust, waist, stomach, abdomen, hip, thigh, lower leg, armhole and elbow, and frequency charts were used to examine Likert scale data of sizing problems. The choices of 12 clothing styles were mapped through four factors which affect the purchasing decision of a plus-size woman.

Poor-fitted clothes at 10 body sites out of the 12 reflected about the fit aspect of plus-size clothing in India. Findings associated to sizing issues like unavailability of trendy clothes in appropriate sizes, which also adorn Indian curvy figure, shows synonymy to the worldwide researcher's findings related to sizing chaos. Classic silhouettes like Straight Indian kurti, A-line dresses and regular-fit trousers were majorly preferred by women. Hiding body bulges was mostly preferred while purchasing loose-fitted garments, and fitted garments were preferred only if these suits to the curvy body proportion. Appropriate fit and size availability are always a prime requisite for this class of women.

The outcomes of research will help Indian retailers/manufacturers to update their patterns in order to provide desired fit. In this lacuna of standard size chart, the study will add value in the development of Indian plus-size women's size chart. The factor mapping with clothing preferences will be useful to reduce rejections and inventories.

For decades, conflict resolution (CR) educators working cross-culturally have struggled with a fundamental dilemma – whether to offer western, evidence-based approaches through a top-down (prescriptive) training process or to use a bottom-up (elicitive) strategy that builds on local cultural knowledge of effective in situ conflict management. This study aims to explore which conditions that prompted experienced CR instructors to use more prescriptive or elicitive approaches to such training in a foreign culture and the implications for training outcomes.

There are two parts to this study. First, the authors conducted a literature review to identify basic conditions that might be conducive to conducting prescriptive or elicitive cross-cultural CR training. The authors then tested the identified conditions in a survey with experienced CR instructors to identify different conditions that afforded prescriptive or elicitive approaches. Exploratory factor analysis and regression were used to assess which conditions determined whether a prescriptive or elicitive approach produced better outcomes.

In general, although prescriptive methods were found to be more efficient, elicitive methods produced more effective, culturally appropriate, sustainable and culturally sensitive training. Results revealed a variety of instructor, participant and contextual factors that influenced whether a prescriptive or elicitive approach was applied and found to be more suitable.

This study used empirical survey data with practicing experts to provide insight and guidance into when to use different approaches to CC-CR training effectively.

In the context of a developing country, Indian buildings need further research to channelize energy needs optimally to reduce energy wastage, thereby reducing carbon emissions. Also, reduction in smart devices’ costs with sequential advancements in Information and Communication Technology have resulted in an environment where model predictive control (MPC) strategies can be easily implemented. This study aims to propose certain preemptive measures to minimize the energy costs, while ensuring the thermal comfort for occupants, resulting in better greener solutions for building structures.

A simulation-based multi-input multi-output MPC strategy has been proposed. A dual objective function involving optimized energy consumption with acceptable thermal comfort has been achieved through simultaneous control of indoor temperature, humidity and illumination using various control variables. A regression-based lighting model and seasonal auto-regressive moving average with exogenous inputs (SARMAX) based temperature and humidity models have been chosen as predictor models along with four different control levels incorporated.

The mathematical approach in this study maintains an optimum tradeoff between energy cost savings and satisfactory occupants’ comfort levels. The proposed control mechanism establishes the relationships of output variables with respect to control and disturbance variables. The SARMAX and regression-based predictor models are found to be the best fit models in terms of accuracy, stability and superior performance. By adopting the proposed methodology, significant energy savings can be accomplished during certain hours of the day.

This study has been done on a specific corporate entity and future analysis can be done on other corporate or residential buildings and in other geographical settings within India. Inclusion of sensitivity analysis and non-linear predictor models is another area of future scope.

This study presents a dynamic MPC strategy, using five disturbance variables which further improves the overall performance and accuracy. In contrast to previous studies on MPC, SARMAX model has been used in this study, which is a novel contribution to the theoretical literature. Four levels of control zones: pre-cooling, strict, mild and loose zones have been used in the calculations to keep the Predictive Mean Vote index within acceptable threshold limits.

This paper analyses the establishment and evolution of a public oversight body (POB) – the Egyptian Audit Oversight Unit (AOU) – and its implications for local auditing firms and practices.

Primary data were gathered from 34 semi-structured interviews (including follow-up ones) between 2014 and 2020. Secondary data was obtained through publicly available documents and internal memos. Drawing on Debord's (1967) Society of the Spectacle, the insights focus on the POB's conception, materialisation and evolution in a context characterised by weak regulatory structures.

Through a series of acts, the findings reveal how the AOU first accepted the image of “international best practice” oversight (the “metaphorical”), followed by the construction of the local structure and décor replicating a United States (US) style POB archetype (the “transformational”) by primarily relying on visible processes/procedures. Yet, these mechanisms emphasised the spectacular nature of oversight, with little improvement for practice and limiting itself to “cracking down” on smaller local firms. A final stage (the “performative”) reveals how the AOU seeks to expand its activities beyond its original mandate without challenging the image-driven nature of its oversight.

The paper offers two key contributions. First, it reveals how actors, through a combination of symbolic and tangible measures, create a new performative reality of public oversight. Second, it advocates Debord's “spectacle” to complement other theoretical lenses, with a view to illuminating the materialisation stages that bridge the gap between proclaimed oversight policies and actual practices (including conscious and unconscious omissions) within a given political economy context.

This paper aims to explore the pathways of carbon transfer in 200 US corporations along with the motivations that drive such transfers. The particular focus is on each firm’s embeddedness in the global value chain (GVC) and the influence of environmental law, operational costs and corporate social responsibility (CSR). The insights gleaned bridge a gap in the literature surrounding GVCs and corporate carbon transfer.

The methodology comprised a two-step research approach. First, the authors used a two-sided fixed regression to analyse the relationship between each firm’s embeddedness in the GVC and its carbon transfers. The sample consisted of 217 US firms. Next, the authors examined the influence of environmental law, operational costs and CSR on carbon transfers using a quantitative comparison analysis. These results were interpreted through the theoretical frameworks of the GVC and legitimacy theory.

The empirical results indicate positive relationships between carbon transfers and GVC embeddedness in terms of both a firm’s position and its degree. From the quantitative comparison, the authors find that the pressure of environmental law and operational costs motivate these transfers through the value chain. Furthermore, CSR does not help to mitigate transfers.

The findings offer insights for policymakers, industry and academia to understand that, with globalised production and greater value creation, transferring carbon to different parts of the GVC – largely to developing countries – will only become more common. The underdeveloped nature of environmental technology in these countries means that global emissions will likely rise instead of fall, further exacerbating global warming. Transferring carbon is not conducive to a sustainable global economy. Hence, firms should be closely regulated and given economic incentives to reduce emissions, not simply shunt them off to the developing world.

Carbon transfer is a major obstacle to effectively reducing carbon emissions. The responsibilities of carbon transfer via GVCs are difficult to define despite firms being a major consideration in such transfers. Understanding how and why corporations engage in carbon transfers can facilitate global cooperation among communities. This knowledge could pave the way to establishing a global carbon transfer monitoring network aimed at preventing corporate carbon transfer and, instead, encouraging emissions reduction.

This study extends the literature by investigating carbon transfers and the GVC at the firm level. The authors used two-step research approach including panel data and quantitative comparison analysis to address this important question. The authors are the primary study to explore the motivation and pathways by which firms transfer carbon through the GVC.

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions” project (BtM). The project combines a computational ontology with a mixed-methods approach drawn from both the social sciences and the humanities, enabling research to be conducted both at scale and in depth, producing complex relational analyses of audiences. BtM aims to understand how we might enable a wide range of audiences to participate in a more diverse film culture, and embrace the wealth of films beyond the mainstream in order to optimise the cultural value of engaging with less familiar films. BtM collects data through a three-wave survey of film audience members’ practices, semi-structured interviews and film-elicitation groups with audience members alongside interviews with policy and industry experts, and analyses of key policy and industry documents. Bringing each of these datasets together within our ontology enables us to map relationships between them across a variety of different concerns. For instance, how cultural engagement in general relates to engagement with specialised films; how different audiences access and/or share films across different platforms and venues; how their engagement with those films enables them to make meaning and generate value; and how all of this is shaped by national and regional policy, film industry practices, and the decisions of cultural intermediaries across the fields of film production, distribution and exhibition. Alongside our analyses, the ontology enables us to produce data visualisations and a suite of analytical tools for audience development studies that stakeholders can use, ensuring the research has impact beyond the academy. This paper sets out our methodology for developing the BtM ontology, so that others may adapt it and develop their own ontologies from mixed-methods empirical data in their studies of other knowledge domains.

Ahmet Kuru, in his book, suggests that the explanation for the lack of social and political development in the modern world can be traced back to a historical ‘state-ulama alliance’ from the 11th-century Saljuq empire or earlier. From the perspective of an historian, however, this dating displays some empirical problems. It is certain that the state eventually did gain the upper hand over the Muslim intellectuals, at least in the centre of the Ottoman empire. But the process to that point was different. In this comment, a different explanation is proposed that points instead to two crucial factors: the loss of a homogeneous Muslim state with the fall of the caliphate, and the rise of a unified Muslim world, an umma, through the independence, not subservience, of the class of scholars in the mediaeval period of Islam. Thus, a model is proposed that focuses on two turning points: the replacement of the effective caliphate with a fractious system of sultanates in the mid-tenth century, coinciding with the solidification of Islamic thought in a more strictly regulated form both in theology, law and in Sufism. The second moment is ca. 1500, when the period of political fragmentation comes to an end with the Ottoman state unifying the Middle East, flanked by Morocco and Iran, while challenges to the religious orthodoxy begin to grow at the margins. Such a model thus sees the ulama as actors for change as well as for orthodoxy throughout Muslim history, responding to changing developments in social and political contexts.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

This study reinvestigates the validity of the Phillips curve in Nigeria for the period 1980–2020 by considering the asymmetric nexus between unemployment and inflation.

The nonlinear autoregressive distributed lag (NARDL) technique was used to decompose the unemployment variable into two components: tight and loosened labour markets.

The empirical outcome shows that unemployment has a significant negative effect on inflation when the labour market is tight and a weakly negative and significant effect on inflation when the labour market is loose. The study confirms an asymmetric Phillips curve in Nigeria since the positive (tight) unemployment rate exerts a greater effect on inflation than the negative (loosened) unemployment rate.

The findings of this study have important implications for implementing monetary policy in Nigeria.

To the best of the authors’ knowledge, this is the first study to investigate the existence of a nonlinear Phillip curve in Nigeria.