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The aims of the article are to not only review existing competency models and offer a comprehensive performance-linked competency model towards sustaining competitive advantage, but also validate the proposed model in an Indian textile organisation.

The article operationalises the term “competency” and intends to develop a comprehensive performance-linked competency model after analysing the existing models with respect to competitive advantage; and the model has been validated empirically in an Indian textile company using data envelopment analysis (DEA), cross-efficiency DEA, and rank order centroid (ROC) methods.

It reveals that the comprehensive performance-linked competency model focuses on competency identification, competency scoring and aligning competency with other strategic HR functions in a three-phase systematic method which will subsequently help the organisation to sustain in the competition. It has further been shown how using DEA, cross-efficiency DEA and ROC, an organisation can align individual performances and their competencies in terms of efficiency.

If the number of competencies get increased, DEA cannot be used.

This can be applied to industry for more efficient and effective performance measurement tool.

The paper enables organizations to systematically manage their employee competences to ensure high-performance level and competitive advantage.

Online search effort is routinely measured by the duration of visit at the website as obtained from clicksream data or surveys. Measuring search effort by the time spent at a website assumes that all consumers who search for the same duration obtain the same amount of information. This would be acceptable if all consumers possessed the same navigational ability. In practice, different consumers have different levels of ability to navigate a website. The purpose of this study is to find whether an individual’s navigational ability has an influence on visit duration and purchase likelihood.

The authors use visit duration data from a real website which makes it possible to partition the visit duration into the times spent on relevant and irrelevant pages. The data were collected through an experimental study. The authors develop an empirical model, comprising hazard and choice models, to assess the relationship between navigational ability and elements of website usage.

A consumer with poor navigational ability spends more time searching on the Web and has lower purchase probability compared to a consumer with superior ability.

The study is limited to one data.

This research has managerial implications for website design, such as link-structure, appearance, size and the number of graphics.

This is the first study to research navigational ability’s influence on online consumer behavior.

Introduction: Human resource management (HRM) is going through a transformation phase due to the pandemic. The COVID-19 crisis compelled the employees to work virtually. To mitigate the effects of COVID-19, several organisations heavily invested in artificial intelligence (AI) in the realm of HRM.

Purpose: With limited studies on the paradigm shift in HRM post-pandemic and the role of AI, the study investigates and proposes a conceptual framework for the paradigm shift in HRM practices post-COVID-19 pandemic and the significance of AI. Furthermore, the study investigates the outcomes of the use of AI in HRM for organisations and employees.

Methodology: A comprehensive review of the literature based on the guidelines of Tranfield, Denyer, and Smart (2003) and Crossan and Apaydin (2010) has been followed. A systematic literature review assisted in critically analysing, synthesising, and mapping the extant literature by identifying the broad themes involved.

Findings: COVID-19-related economic disruption has led to a paradigm shift in HRM practices. AI-enabled HRM practices are now centred around remote and contingent workforce management, mindfulness, social capital, increasing employee engagement, reskilling and upskilling towards new competencies, etc. AI is making remote work seamless through smooth recruitment and selection process, onboarding, career and development, tracking and managing the performance, facilitating learning, and talent management. Post-pandemic, AI-powered tools based on data mining (DM), predictive analytics, big data analytics, natural language processing (NLP), intelligent robots, machine learning (ML), virtual (VR)/augmented reality (AR), etc., have paved the way for managing the HRM practices effectively, thereby leading to enhanced organisational performance, employee well-being, automation, and reduced cost.

The purpose of this paper is to explore the relationship between competency-based performance management and organizational effectiveness (OE). It signifies the importance of developing competency-based performance concept in organizations. Since conventional performance management systems (PMSs) are diminishing and as organizations are looking for breakthrough PMSs, this research attempted to fill the gap from stakeholder’s perspective – employee, manager and organization in devising new approach in PMS.

The research design involved developing scale for “competency-based superior performance” and validating scale for “organizational effectiveness,” The data for this survey are collected from 292 respondents through structured questionnaire. Hypotheses depicting aforementioned relationships were empirically tested in the context of competency-based performance practices in organizations based in India. Structural equation modeling (SEM) technique was used for data analysis.

The empirical results provide methods to accelerate the performance management initiatives based on a leadership competency model (LCM), which are necessary for building performance culture in the organization. The paper contributes by developing a new scale for measuring competency-based performance practices. The scale for OE is revisited. A positive relationship between competency-based superior performance and OE with productivity, adaptability and flexibility has been empirically confirmed using SEM.

The paper limits the performance measurement concept using leadership competencies.

The developed model will act as a building block for performance measurement in organizations. This paper promotes LCM to be applied in creating a performance-based culture.

This is a unique attempt to test the relationship between competency-based performance management and OE.

Narendra Modi’s Bharatiya Janata Party made fighting corruption as a major election plank, and won the 2014 elections, and formed the National Democratic Alliance government – a majority party government in India in nearly 30 years. Modi was re-elected in May 2019 with a bigger majority. As his government celebrates the second term, it is time to assess the last five years’ accomplishments in fighting corruption. This chapter deals with the subject under four major headings. The first examines the efficacy of existing anti-corruption agencies. The second explains the office of Lokpal (Ombudsman). The third analyses the initial challenges and efforts of the Modi government. The fourth draws some conclusions.

Resurgent interest in the life and work of the Italian Cambridge economist Piero Sraffa is leading to New Directions in Sraffa Scholarship. This chapter introduces readers to some of these developments. First and perhaps foremost is the fact that as of September 2016 Sraffa’s archival material has been uploaded onto the website of the Wren Library, Trinity College, Cambridge University, as digital colour images; this chapter introduces readers to the history of these events. This history provides sharp relief on the extant debates over the role of the archival material in leading to the final publication of Production of Commodities by Means of Commodities, and readers are provided a brief sketch of these matters. The varied nature of Sraffa scholarship is demonstrated by the different aspects of Sraffa’s intellectual legacy which are developed and discussed in the various entries of our Symposium. The conclusion is reached that we are on the cusp of an exciting phase change of tremendous potential in Sraffa scholarship.

This chapter addresses one aspect of the broad issue of the psychological foundations of the dimensions of multidimensional scaling (MDS) solutions. Using empirical data from three independent studies, it is shown that the dimensionality of MDS solutions is negatively related to individual differences in the level of cognitive differentiation and integrative complexity of individuals and positively related to the individual's ability to discriminate within dimensions. MDS dimensionality is also shown to be affected by a variety of task-related variables such as perceived task difficulty, consistency in providing similarity judgments, confidence, familiarity, and importance attached to the stimuli. The chapter concludes by raising the issue of whether MDS can be validly used to describe complex cognitive processes.

Flowers and fruits of Madhuca longifolia (Koenig) (mahua) tree are edible and used as traditional Indian medicines. The physicochemical properties of different parts of mahua are investigated. This study aims to estimate the different mineral contents, polyphenols compounds and antioxidant activities by 2,2-diphenyl-1-picrylhydrazyl inhibition, reducing power, free radical scavenging activity using 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid) and ferric reducing antioxidant power assays of mahua flower, ripe and unripe fruit.

Flavonoids were identified and quantified in yellow flowers and fruits of M. longifolia tree by high-performance liquid chromatography with diode array detector. Low molecular weight carbohydrates were determined by the ICBio scan, a specific method for determining of carbohydrates. Mineral content is determined by laser-induced breakdown spectroscopy (LIBS) and atomic absorption spectroscopy. Physicochemical, nutritional and mineral properties of mahua flower, ripe and unripe fruit were investigated by the statistical approach of principal component analysis (PCA).

Ascorbic acid, gallic acid (GA), quercetin and myrcetin were the phenolic compounds identified and quantified in mahua flower and fruit extracts. Sugar profiling of mahua flowers and fruits confirmed the presence of inositol, sorbitol, mannitol, dextrose, fructose, sucrose, raffinose and maltose. The mineral content of Na, K, Mg and Ca was present in quite a good amount in all samples. Total phenolic content (TPC) was significantly high in mahua flower (25.3 ± 1.0 mg GA equivalent/g FW) followed by mahua unripe (15.8 ± 1.0 mg GA equivalent/g FW) and ripe fruit (14.3 ± 1.0 mg GA equivalent/g FW) at p = 5%. In contrast, total flavonoid contents (TFCs) were highest in ripe fruit, then mahua flower and unripe fruit. Positive correlations were predicted by PCA for mahua flower with TPC, antioxidant activity assays and minerals except for Na; ripe fruit with TFC and Na; and unripe fruit with maltose and sorbitol.

This study demonstrates the application of LIBS for the determination of elements present in the mahua flowers and fruits and reveals that mahua can be a good source of nutrients. Sugar profiling of mahua flower showed that it is a rich source of reducing and non-reducing sugar, proving that mahua flower juice can be used as a natural sweetener in the development of different food products, namely, biscuits, cookies, cake, jam, jelly, juice and squash.

The purpose of this paper is to conduct an experimental investigation on the shock cell structure of jets emanating from a four-lobed corrugated nozzle using Schlieren imaging technique.

The Schlieren images were captured for seven different nozzle pressure ratios (NPR = 2, 3, 4, 5, 6, 7 and 8) and compared with the shock cell structure of a round nozzle with an identical exit area. The variation in the length of the shock cell, width of boundary interaction between adjacent shock cells, maximum width of first shock cell, Mach disk position and diameter for different NPR was measured from the Schlieren images and analysed.

A three-layer shock net observed in the jet emanating from the four-lobed corrugated nozzle is a novel concept in the field of under-expanded jet flows. A shock net represents interconnected layers of shock cells developed because of the interaction between the core and peripheral shock waves in a jet emanating from a corrugated lobed nozzle. Also, the pattern of shock net is different while taking Schlieren images across the groove and lobe sections. Thus, the shock net emerging from a corrugated lobed nozzle varies azimuthally and primarily depends on the nozzle exit cross section. The length of the shock cell, width of boundary interaction between adjacent shock cells, maximum width of first cell, Mach disk position and diameter were found to exhibit increasing trend with NPR.

A novel concept of interconnected layers of shock waves defined as “shock net” developed from a single jet emanating from a four-lobed corrugated nozzle was observed.

The chapter explored the critical components, challenges, and technological advancements in construction supply chain management (CSCM), focusing on stealth construction (STC). It delved into STC encompassing nature, highlighting its unique challenges in its supply chain management and the necessity for adaptive technologies. It further discussed the benefits of tailoring supply chain management specifically for STC, emphasising the importance of developing the building’s cross-section, managing visibility, controlling energy transmission, and implementing countermeasures. Practical applications of CSCM in STC are also examined. This chapter sheds light on the complexities of managing supply chains in STC contexts and offers insights into strategies and technologies to address these challenges effectively.