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Marketing Management, Consumer Behavior.

This case is suitable to be used in advanced undergraduate and MBA/MSc level.

This case attempts to highlight the issues pertaining to Hirdaramani Mihila CKT apparel factory’s implementation of the “green space” concept. The concept of “green space” has been well accepted by the factory employees, and their participation in the “green process” is quite evident. Hirdaramani Mihila CKT is an apparel manufacturing company located in Agalawatte, Matugama, in the Kalutara District of Sri Lanka. The Mihila CKT factory was established in conformance with green building specifications and as an eco-friendly apparel industry. The administration of Mihila CKT has achieved success in three key areas after implementing this concept: cutting down energy consumption, enhancing water security, and reusing fabric waste. The factory also maintains a garden that manifests biodiversity. This case underlines the challenges and successes faced by Mihila CKT in adopting and implementing green space concept.

This case illustrates the following:

• the importance of having green technology in the apparel industry to embrace green concept;

• the effectiveness of the green space concept in relation to global green standards; and

• the potential benefits to the local residents from the green technology initiatives of an apparel factory like Hirdaramani Mihila CKT.

the importance of having green technology in the apparel industry to embrace green concept;

the effectiveness of the green space concept in relation to global green standards; and

the potential benefits to the local residents from the green technology initiatives of an apparel factory like Hirdaramani Mihila CKT.

Examines the tenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

This study investigates the repetitive mixed sampling (MRS) plan based on the Cpk index that was proposed by Aslam et al. (2013a). They were the first to study the MRS plan, but they did not pay attention to the fact that submitting to the variable inspection a sample that was first submitted to the attribute inspection, truncates the X observations. In addition, they did not work with an accurate expression to calculate the probabilities of the Cpk statistic.

The authors presented the results based on their original sampling plan through Monte Carlo simulation and defined the theoretical results of their plan when the sample submitted to the variable inspection is no longer the same one submitted to the attribute inspection.

The β risks of the optimum sampling plans presented by Aslam et al. (2013a) are pretty high, exceeding 46%, on average – this same problem was also observed in Saminathan and Mahalingam (2018), Balamurali (2020) and Balamurali et al. (2020), where the β risks of their proposed sampling plans are yet higher.

In terms of originality, the authors can declare the following. It is not a big deal to propose new sampling plans, if one does not know how to obtain their properties. The miscalculations of the sampling plans risks are dangerous; imagine the situation where the acceptance of bad lots exceeds 50% just because the sampling plan was incorrectly designed. Yes, it is a big deal to warn that this type of problem is arising in a growing number of papers. The authors of this study are the pioneers to discover that many studies focusing on the sampling plans need to be urgently revised.

Dementia in older persons with learning disabilities is a growing concern for all those involved in their care. There is at present no effective treatment, but the importance of current drug treatments is reviewed. Developments in drug treatments for dementia remain an active area of ongoing research.

Purpose: Risk is a multifaceted concept, and its identification requires complex approaches that are often misunderstood. The consequence is that decisions are based on limited perception rather than the full value and meaning of what risk is, as a result, the way it is being tackled is incorrect. The individuals are often limited in their perceptions and ideas and do not embrace the full multifaceted nature of risk. Regulators and individuals want to follow norms and checklists or overuse models, simulations, and templates, thereby reducing responsibility for decision-making. At the same time, the wider use of technology and rules reduces the critical thinking of individuals. We advance the automation process by building robots that follow protocols and forget about the part of risk assessment that cannot be programed. Therefore, with this study, the objective of this study was to discover how people define risk, the influencing factors of risk perception and how they behave toward this perception. The authors also determine how the perception differed with age, gender, marital status, education level and region. The novelty of the research is related to individual risk perception during COVID-19, as this is a new and unknown phenomenon. Methodology: The research is based on the analysis of the self-administered purposely designed questionnaires we distributed across different social media platforms between February and June 2020 in Europe and in some cases was carried out as a interview over communication platforms such as “Skype,” “Zoom” and “Microsoft Teams.” The questionnaire was divided into four parts: Section 1 was designed to collect demographic information from the participants; Section 2 included risk definition statements obtained from literature and a preliminary discussion with peers; Section 3 included risk behavior statements; and Section 4 included statements on risk perception experiences. A five-point Likert Scale was provided, and participants were required to answer along a scale of “1” for “Strongly Agree” to “5” for “Strongly Disagree.” Participants also had the option to elaborate further and provide additional comments in an open-ended box provided at the end of the section. 466 valid responses were received. Thematic analysis was carried out to analyze the interviews and the open-ended questions, while the questionnaire responses were analyzed using various quantitative methods on IBM SPSS (version 23). Findings: The results of the analysis indicate that individuals evaluate the risk before making a decision and view risk as both a loss and opportunity. The study identifies nine factors influencing risk perception. Nevertheless, it must be emphasized that we can continue to develop models and rules, but as long as the risk is not understood, we will never achieve anything.

Despite its central role in the influence process, power has largely been overlooked by scholars seeking to understand global leaders' influence over their constituents. As a consequence, we currently have limited understanding of the varieties of power that global leaders hold, how power is exercised in global contexts, and what impact exercising power has in global organizations. The intended purpose of this chapter is to mobilize research on this important topic through systematic review. The review is organized around the following guiding questions: (i) how is power defined in global leadership research? (ii) what power bases do global leaders possess? (iii) how do global leaders exercise power? (iv) what factors influence global leaders' exercise of power? and (v) what are the outcomes of global leaders' exercise of power? Based on a synthesis of extant insights, this chapter develops a foundation for future research on power in global leadership by mapping critical knowledge gaps and outlining paths for further inquiry.

The pay-as-you-go approach to data integration aims to reduce the time and effort required by proposing a bootstrap phase in which algorithms, rather than experts, identify semantic correspondences and generate the mappings. This highly automated bootstrap phase is likely to be of low quality, thus pay-as-you-go approaches postulate a subsequent continuous improvement phase based on user feedback assimilation to improve the quality of the integration. The purpose of this paper is to quantify the quality of a speculative integration, using one particular type of feedback, mapping results, whilst taking into account the uncertainty of user feedback provided.

The authors propose a systematic approach to quantify the quality of an integration as a conditional probability given the trustworthiness of the workers. Given a set of mappings and a set of workers of unknown trustworthiness, feedback instances are collected in the extents of the mappings that characterize the integration. Taking into account the available evidence obtained from worker feedback, the technique provides a quality quantification of the speculative integration.

Experimental results on both synthetic and real-world scenarios provide valuable empirical evidence that the technique produces a cost-effective quantification of integration quality that faithfully reflects the judgement of the workers whilst taking into account the inherent uncertainty of user feedback.

Current pay-as-you-go techniques provide a limited view of the integration quality as the result of feedback assimilation. To the best of the authors’ knowledge, this is the first proposal for quantifying integration quality in a systematic and principled manner using mapping results as a piece of evidence while at the same time considering the uncertainty inherited from user feedback.

This paper aims to explore the optimization process involved in the aircraft maintenance allocation and packing problem. The aircraft industry misses a part of the optimization potential while developing maintenance plans. This research provides the modeling foundation for the missing part considering the failure behavior of components, costs involved with all maintenance tasks and opportunity costs.

The study models the cost-effectiveness of support against the availability to come up with an optimization problem. The mathematical problem was solved with an exact algorithm. Experiments were performed with real field and synthetically generated data, to validate the correctness of the model and its potential to provide more accurate and better engineered maintenance plans.

The solution procedure provided excellent results by enhancing the overall arrangement of the tasks, resulting in higher availability rates and a substantial decrease in total maintenance costs. In terms of situational awareness, it provides the user with the flexibility to better manage resource constraints while still achieving optimal results.

This is an innovative research providing a state-of-the-art mathematical model and an algorithm for efficiently solving a task allocation and packing problem by incorporating components’ due flight time, failure probability, task relationships, smart allocation of common preparation tasks, operational profile and resource limitations.