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Logistics may be defined as the provision of goods and services from a supply point to a demand point. In recent times the cost of transport has become a major expense for organizations as a result of escalating fuel costs and higher capital costs for the replacement of vehicles. Hence vehicle routeing in an organization has become an important managerial function for the availability of transport facilities, minimizing the late arrival of the vehicles and providing good service to the employees. Discusses the formulation, solution algorithms, and implementation strategies to be followed in vehicle routeing in a public sector undertaking in India, employing 7,861 people. The well known Clarke and Wright algorithm has been used to obtain the initial solution, and the norms formulated by the management are used to help implement the action plans so as to improve vehicle‐routeing efficiency. Highlights specific financial and other benefits on application of the required routeing. Also mentions some of the limitations of the approach.

This study aims to analyze how Indian management practices have influenced the international management research agenda. International interest in India as a business destination has been growing since the Indian policy-makers began opening up the economy in 1991. India’s continuing economic development and integration with global economy has led to a reassessment of its political, social and commercial relevance by the international community.

The authors choose four management disciplines and examine 40 peer-reviewed international journals for research related to India over the period 1991-2014. From the sample of 217 papers, the authors identify the trends, themes and motivations, and discuss the potential for future research.

The authors find that research on India remains flat for the 1991-2000 decade, and starts growing from 2005 onwards. Organizational behavior remains non-participative in the overall growth of research. The authors find very low levels of qualitative research, and none on endogenous phenomena that have been tested for applicability in non-Indian contexts. Marketing research remains mainly peripheral to Indian contexts. Review of highly cited papers reveals that management research on India is at an early stage, and offers fairly significant opportunities for future researchers.

Normal limitations of sample-based literature review apply. Further, the literature search is limited to a select set of highly ranked journals.

Studies analyzing themes related to Indian contexts in international publications are sparse. To the best of authors’ knowledge, no study of this nature exists in literature. This study makes a primary contribution for future management researchers across the four areas by informing on the research trends, journal outlets, and the characteristics of the research agenda.

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.

Utilising industrial waste, such as fly ash (FA) and bagasse ash (BA), reduces waste management and increases mechanical strength. Concrete is modified with FA and BA in the cool bonded method of concrete preparation.

The study used to partially replace cement with BA powder at proportions 0, 5, 10, 15, 20 and 25% and coarse aggregates are replaced with FA aggregates made with FA and cement using a cold-bonded technique at proportions 0–25%. FA aggregates were made at 10:90, 15:85, 20:80 and 25:75 proportions of cement and FA. The FA aggregates at the best proportion 15:85 was selected as a coarse aggregate by conducting tests like specific gravity, crushing value, impact value and water absorption tests.

The addition of 30% content decreases porosity by 21% and increases strength significantly at 28 days. Microstructure evolution is carried out to identify material behaviour.

Mechanical and durable properties such as flexural strength, tensile strength, water absorption test, acid and alkaline tests are conducted on M50 grade concrete after 3–28 days of curing.

Organizational psychologists and human resource management (HRM) practitioners often have to select the “right fit” candidate by manually scouting data from various sources including job portals and social media. Given the constant pressure to lower the recruitment costs and the time taken to extend an offer to the right talent, the HR function has to inevitably adopt data analytics and machine learning for employee selection. This paper aims to propose the “Quality of Hire” concept for employee selection using the person-environment (P-E) fit theory and machine learning.

The authors demonstrate the aforementioned concept using a clustering algorithm, namely, partition around mediod (PAM). Based on a curated data set published by the IBM, the authors examine the dimensions of different P-E fits and determine how these dimensions can lead to selection of the “right fit” candidate by evaluating the outcome of PAM.

The authors propose a multi-level fit model rooted in the P-E theory, which can improve the quality of hire for an organization.

Theoretically, the authors contribute in the domain of quality of hire using a multi-level fit approach based on the P-E theory. Methodologically, the authors contribute in expanding the HR analytics landscape by implementing PAM algorithm in employee selection.

The proposed work is expected to present a useful case on the application of machine learning for practitioners in organizational psychology, HRM and data science.

The author aims to develop an employee competency framework for a volatility, uncertainty, complexity and ambiguity (VUCA) environment and propose learning and development (L&D) interventions for organisations and employees to develop competencies for thriving in a VUCA environment.

The framework synthesis method was used to determine employee competencies that are essential in a VUCA world.

The author identified 10 competencies that are essential for employee development in a VUCA world. The author categorised these employee competencies as cognitive (cognitive flexibility, agility mindset and personal ambidexterity), cross-cultural (cross-cultural intelligence and cross-cultural collaboration), analytical (creativity and complex problem solving) and personal effectiveness competencies (personal resilience, continuous learning and adaptive mindset).

The proposed competencies could be used for the personal development of employees and organisations. The VUCA competency framework developed in this study includes behavioural dimensions for each competency, which could be used in self-assessment, recruitment and selection and talent and performance management. Furthermore, the author proposes L&D interventions required for developing these competencies. Overall, this study contributes to human resources (HR) development in the VUCA era by proposing the development of specific individual competencies as necessary conditions for survival and growth.

VUCA competencies empower employees to not only survive but also thrive in an unpredictable and rapidly changing world. By incorporating these competencies in L&D interventions, organisations can help employees develop the necessary competencies to thrive in a VUCA environment, thus contributing to their personal and organisational success.

This study aims to explore the challenges experienced by managers in adopting competency modeling (CM) and recommends an approach to overcome these challenges in promoting competency-based intellectual capital in organizations.

Using in-depth interviews with organizational practitioners in India, this study identifies the challenges of competency modeling in emerging market economies.

This study identified nine contextual and eight non-contextual challenges in implementing CM practices in organizations. The framework addresses the CM challenges using direction setting, negotiation and selling, and monitoring and control dimension of implementation with behavioral, operational and change alignment aspects of CM. The framework proposes a checklist for stakeholders to help them diagnose and analyze the gaps in effective CM implementation.

This article contributes in the concept of competency-based intellectual capital and adoption of CM practices.

This framework will assist the change management practitioners, human resources leaders, organizational development consultants and practitioners as a toolkit to address the challenges in the people management intervention.

The framework suggests a checklist for stakeholders to help diagnose and analyze the gaps in effective CM adoption.

Aerospace and defence industries use the materials having better properties at elevated temperatures, and Inconel 718 is one of that. The complexity in realizing complex and intricate shapes necessitate the product realization through additive manufacturing. This paper aims to investigate the wear behaviour of additive manufactured material.

The wear behaviour of additively manufactured Inconel 718 samples through direct metal laser sintering process at three different build orientations was experimentally investigated using a standard pin-on-disc wear tester.

Among the varied wear parameters, the load was identified as the most influencing parameter on the wear rate. In addition, the post-failure analysis of the worn surface of the pins under the scanning electron microscopy revealed the presence of various wear mechanisms.

Almost, the industries are now focussed on their production through additive manufacturing owing to its advantages. The present work displays the wear behaviour of the additive manufactured Inconel 718 and its associated wear mechanisms.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0322.

Introduction: Artificial intelligence (AI) assists recruiters in effectively and efficiently nominating applicants precisely and accurately. It helps in the screening of resumes without biasness. This chapter will identify different AI technology and various organisations using it fully or partially.

Purpose: This chapter aims to get insights about various AI tools that assist human recruiters, save time and cost, and provide modern experiences. It will help identify various applications that are currently in use and their features. It also helps in finding out the benefits and the challenges faced by the recruiters and the applicants while assimilating those applications in hiring.

Need for the Study: The study will be helpful to all those recruiting firms who are presently using AI or not using it to understand the benefits and challenges they might face.

Methodology: The chapter will be based on reviews and industry reports. This chapter will include a study related to human resource (HR) functions where AI is used. To give more insights into AI technology, this study mentions various applications like Mya, Brazen, etc., and their usefulness in recruitment. Also, special emphasis would be given to the recruitment functions as most companies use AI. Some companies like Deloitte and Oracle are using AI fully or partially will also be incorporated.

Findings: The study finds out that although many companies have started to use AI tools for recruitment, they have not explored all the algorithms that can be used to complete the whole recruitment and selection process. Companies like Loreal use AI for candidate applications and recruiter screening, but human recruiters stand strong for assessments and interviews. AI’s widespread use presents human resource management (HRM) practitioners with both opportunities and challenges.

Practical implications: The basic idea of the study is to scrutinise the related literature and find out the features, advantages and limitations/challenges of using AI which would be helpful for recruiters in better understanding of the technology-driven recruitment.

The purpose of this paper is to present a weakly supervised learning method to perform health evaluation and predict the remaining useful life (RUL) of rolling bearings.

Based on the principle that bearing health degrades with the increase of service time, a weak label qualitative pairing comparison dataset for bearing health is extracted from the original time series monitoring data of bearing. A bearing health indicator (HI) quantitative evaluation model is obtained by training the delicately designed neural network structure with bearing qualitative comparison data between different health statuses. The remaining useful life is then predicted using the bearing health evaluation model and the degradation tolerance threshold. To validate the feasibility, efficiency and superiority of the proposed method, comparison experiments are designed and carried out on a widely used bearing dataset.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.

The method achieves the transformation of bearing health from qualitative comparison to quantitative evaluation via a learning algorithm, which is promising in industrial equipment health evaluation and prediction.