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These days vehicles' spare parts (SPs) are a very big market, and there is a very high demand for these parts. Forecasting vehicles' SPs price and demand are difficult because of the lack of data and the pricing of the SPs is not following the normal value chain methods like normal products.

A proposed model using multiple linear regression was developed as a guide to forecasting demand and price for vehicles' SPs. A case study of selected hybrid vehicle is held to validate the results of the research. This research is an original study depending on quantitative and qualitative methods; some factors are generated from realistic data or are calculated using numerical equations and the analytic hierarchy process (AHP) method; online questionnaire and expert interview survey.

The price and demand for SPs have a linear relationship with some independent variables is the hypothesis that is tested. Even though the proposed models are generally recommended for predicting demand and price, in this research the linear relationship models are not significant enough to calculate the expected price and demand.

This research should concern both academics and practitioners since it provides new intuitions on the distinctions between scientific and industrial world regarding SPs for vehicles as it is the first study that investigates price and demand of vehicles' SPs.

This article presents a comprehensive analysis of innovation in micro, small and medium enterprises (MSMEs) in India, focusing on the barriers and facilitators within their internal and external ecosystems.

A self-administered questionnaire was used to collect data from 1430 MSMEs across India, employing Structural Equation Modeling (SEM) to analyze the relationships between internal and external factors and innovation adaptation.

The findings indicate that factors such as top management and organization structure, communication, technological capability and adaptation and organizational culture have a positive impact on innovation adaptation within the internal environment. Conversely, employee and market orientation, as well as financial factors, have a negative influence. Regarding the external environment, industry and competitive analysis, internationalization and partner alliances were found to positively affect innovation adaptation, whereas the country's infrastructure and policies had a negative impact.

The study emphasizes that MSMEs have the potential to leverage their internal and external environments to foster innovation within their organizations.

This study aims to identify the present research trends and streamline future research possibilities in luxury brands by a systematic review of the existing literature.

A portfolio of 552 articles published between 1996 and 2020 in the luxury brands domain is collected from the Scopus database and analyzed using an integrated approach comprising bibliometric and content analyses.

A comprehensive review of the available literature was done by identifying emerging topics, keywords and research themes. The study's findings indicate that the luxury brand is an exponentially growing theme; seven representative research clusters are identified and analyzed.

This study enriches the literature of luxury brand by presenting a holistic view of the academic literature using an integrated research methodology comprising bibliometric and content analysis techniques.

This paper aims to identify the current research trends and set the future research agenda in the area of human resource (HR) analytics by an extensive review of the existing literature. The paper aims to capture state of the art and develop an exhaustive understanding of the theoretical foundations, concepts and recent developments in the area.

A portfolio of 125 articles collected from the Scopus database was systematically analyzed using a two-tier method. First, the evolution, current state of the literature and research clusters are identified using bibliometric techniques. Finally, using content analysis, the research clusters are studied to develop the future research agenda.

Based on the bibliometric analysis, network analysis and content analysis techniques, this study provides a comprehensive review of the existing literature. The study also highlights future research themes by identifying knowledge gaps based on content analysis of research clusters.

The evolution and the current state of the HR analytics literature are presented. Some specific research questions are also provided to help future research.

This study enriches the literature of HR analytics by integrating bibliometric analysis and content analysis to develop a more systematic and exhaustive understanding of the research area. The findings of this study may assist fellow researchers in furthering their research in the identified research clusters.

An original systematic review of the academic literature on applications of artificial intelligence (AI) in the human resource management (HRM) domain is carried out to capture the current state-of-the-art and prepare an original research agenda for future studies.

Fifty-nine journal articles are selected based on a holistic search and quality evaluation criteria. By using content analysis and structural concept analysis, this study elucidates the extent and impact of AI application in HRM functions, which is followed by synthesizing a concept map that illustrates how the usage of various AI techniques aids HRM decision-making.

A comprehensive review of the AI-HRM domain’s existing literature is presented. A concept map is synthesized to present a taxonomical overview of the AI applications in HRM.

An original research agenda comprising relevant research questions is put forward to assist further developments in the AI-HRM domain. An indicative preliminary framework to help transition toward ethical AI is also presented.

This study contributes to the literature through a holistic discussion on the current state of the domain, the extent of AI application in HRM, and its current and perceived future impact on HRM functions. A preliminary ethical framework and an extensive future research agenda are developed to open new research avenues.

Drawing on the symbolic interaction theory, this research examines leader–member exchange (LMX) and employee’s happiness at work (HAW) with mediation of self-esteem (SE) and moderation of organizational embeddedness (OE).

The study uses data collected from a sample of 246 employees working in fast moving consumer goods companies (FMCGs) and applied SmartPLS to analyze the proposed model.

Findings reveal that LMX predicts HAW. Whereas, the follower’s SE fully transmitted the effect of LMX on employee’s HAW. Moreover, OE moderated the relationship between LMX and HAW.

Leaders should consider quality LMX interactions with their employees in prevailing global crises. LMX can improve the relationship with team members and boost their SE resulting in HAW. Furthermore, organizations should promote such practices which may enhance their employees' OE for enhanced workplace happiness.

The study is among the very few works which apply symbolic interaction as an overarching framework to explain the employees' HAW.

The study examines the mediating effect of knowledge management (KM) in the relationship between the high-performance organisation (HPO) framework and high performance in financial institutions (FIs) in Uganda. The paper aims to develop a framework that promotes high performance in the FIs.

The conceptual model was tested on a sample of 28 financial instituitions using structural equation model.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

The findings revealed that the high-performance framework is significantly related to high performance and KM is related high performance. KM mediates the relationship between the high-performance framework and high performance.

This study makes several empirical and theoretical contributions, addressing the gap in the literature about the role of the HPO framework in strategic management. This study tests the relationship between the HPO and the firm's performance by taking the mediating effects of KM. The designed model highlights a significant organisational performance approach that can influence the finance sector positively.

Data mining along with its varied technologies like numerical mining, textual mining, multimedia mining, web mining, sentiment analysis and big data mining proves itself as an emerging field and manifests itself in the form of different techniques such as information mining; big data mining; big data mining and Internet of Things (IoT); and educational data mining. This paper aims to discuss how these technologies and techniques are used to derive information and, eventually, knowledge from data.

An extensive review of literature on data mining and its allied techniques was carried to ascertain the emerging procedures and techniques in the domain of data mining. Clarivate Analytic’s Web of Science and Sciverse Scopus were explored to discover the extent of literature published on Data Mining and its varied facets. Literature was searched against various keywords such as data mining; information mining; big data; big data and IoT; and educational data mining. Further, the works citing the literature on data mining were also explored to visualize a broad gamut of emerging techniques about this growing field.

The study validates that knowledge discovery in databases has rendered data mining as an emerging field; the data present in these databases paves the way for data mining techniques and analytics. This paper provides a unique view about the usage of data, and logical patterns derived from it, how new procedures, algorithms and mining techniques are being continuously upgraded for their multipurpose use for the betterment of human life and experiences.

The paper highlights different aspects of data mining, its different technological approaches, and how these emerging data technologies are used to derive logical insights from data and make data more meaningful.

The paper tries to highlight the current trends and facets of data mining.

While the world grappled with the COVID-19 pandemic and its externalities, scientists have recommended that the global community brace against potential future pandemics. The need to build resilient systems has never been this urgent. The world, especially emerging economies, faces acute food insecurity, high food prices, failing health infrastructure and rampant misinformation spread, among others. Since blockchain technology (BCT) has been discussed in the supply chain resilience context, and it offers the potential to develop resilient systems, we aim to outline the potential of BCT to help build resilience against ongoing and future pandemics. Mainly, we focus on BCT for healthcare management, disruption management of food supply chains, human resource management, modern education and certification and governance and administration.

This paper aims to review and discuss four aspects of mixed-model assembly line balancing (MMALB) problem mainly on the optimization angle. MMALB is a non-deterministic polynomial-time hard problem which requires an effective algorithm for solution. This problem has attracted a number of research fields: manufacturing, mathematics and computer science.

This paper review 59 published research works on MMALB from indexed journal. The review includes MMALB problem varieties, optimization algorithm, objective function and constraints in the problem.

Based on research trend, this topic is still growing with the highest publication number observed in 2016 and 2017. The review indicated that the future research direction should focus on human factors and sustainable issues in the problem modeling. As the assembly cost becomes crucial, resource utilization in the assembly line should also be considered. Apart from that, the growth of new optimization algorithms is predicted to influence the MMALB optimization, which currently relies on well-established algorithms.

The originality of this paper is on the research trend in MMALB. It provides the future direction for the researchers in this field.