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This study aims to investigate gamification-based training program through the lens of self-determination theory and in the context of corporate training programs. It integrates the self-determination theory, game elements and learning outcomes in gamified training programs to derive insights.

Data is sourced from software development companies operating in the city of Bangalore in India. It applies the partial least square structural equation modeling to investigate the relationship between the self-determination learning theory and game elements and the impact it has on learning outcomes.

As a precursor to the development of a game-like learning ecosystem, the authors study the perception of trainers and human resource managers toward game-based training programs in the organization. The authors find that game-based learning makes training more engaging, immersive and contextual for the learners.

The study is based on a specific sector, i.e. software development companies, and so the results may lack in generalizability. Future research, therefore, may consider other industrial sectors such as manufacturing, banking and telecom to understand the relationship between the constructs.

This study provides insights for the trainers, human resource managers and academicians on the effectiveness of gamification-based training programs. It also provides information on how the learning theory can be leveraged to understand gamification-based training programs.

This work fulfills an identified need of the training industry to understand new methods of training with an aim to improve the learning outcomes among the learners.

This study provides a deep understanding on the effectiveness of training tools such as gamified training programs in enhancing and improving the learning outcomes among the learners.

The purpose of this paper is to provide the insights on the challenges influencing rural start-ups. It provides insights with regards to managerial, operational, marketing and finance-related challenges influencing the rural start-ups in the study. The study aims to expand the domain of start-ups by including a broader range of challenges and related aspects found in the start-up literature.

The paper opted for an exploratory study using the open-ended approach of grounded theory, including 61 rural start-ups operating in Karnataka, India. The data were analysed through non-parametric test to understand the comparison between different sectors of rural start-ups.

It suggests that marketing techniques and infrastructure challenges influences the rural start-ups. Therefore, success of start-ups is influenced by these related variables.

Because of the chosen research approach, the research results may lack generalizability. Researchers are therefore encouraged to test the proposed propositions further in the area of challenges and growth in the domain of managerial, infrastructure, marketing, finance, human resource and logistics in rural start-ups. The study is restricted to rural start-ups located in districts of Karnataka, India.

The paper includes implications for managing the challenges for enhancing the growth of start-ups. The paper provides insights on the significant challenges witnessed by the start-ups and provides directions for the growth of start-ups.

This paper fulfils an identified need of the start-ups in rural sector and contribute to the growth of start-ups in rural sector of India.

This paper fulfils an identified need to study how rural start-ups operate and create a niece in the growth of Indian economy.

This study aims to examine factors that determine the adoption of additive manufacturing by small- and medium-sized industries. It provides insights with regard to benefits, challenges and business factors that influence small- and medium-sized industries when adopting this technology. The study also aims to expand the domain of additive manufacturing by including a broader range of challenges and benefits of additive manufacturing in literature.

Using data collected from 175 small- and medium-sized industries, the study has examined through Mann–Whitney test to understand the difference between owners and design engineers on additive manufacturing technology adoption in small- and medium-sized companies.

This study suggests contribution to academic discussion by providing associated factors that have significant impact on the adoption of additive manufacturing technology. Related advantages of additive manufacturing are reduction in inventory cost, lowering the wastage in production and customization of products. The study also indicates that factors such as cost of machinery, higher level of cost in integrating metal components have a negative impact on the adoption of this technology in small- and medium-sized industries.

Because of the chosen research approach, the research results may lack generalizability. Therefore, researchers are encouraged to test the proposed propositions further in the field of challenges and growth in other areas of application of additive manufacturing, for instance, medical sciences, fabric and aerospace.

The study provides important implications that are of interest for both research and practitioners, related to technology management in small- and medium-sized industries, e.g. foundry and machining industries.

This work/study fulfills an identified need of the small- and medium-sized companies in adopting new technologies and contribute to their growth by understanding the need to accept and implement technology.

This paper fulfills an identified need to study how small- and medium-scale companies accept new technologies and factors associated with implementation in the manufacturing process of the organization.

The paper aims to provide insights into the influence of COVID-19 on employee engagement and ergonomics in the banking sector. The purpose of this study is understood from the perspective of impact of the pandemic on banking employees.

Data for the study are collected from the employees working in the banking sector of India. The study applied the partial least squares (PLS) method of analysis to understand the relationship between employee engagement and ergonomics in the banking sector.

The findings of the study suggest results with regards to change in the perception of the employees in the bank and its influence on the work ergonomics due to pandemic. The findings indicate that banks need to develop measures and strategies for improving employee engagement programs and work ergonomics at banks.

The study is confined to the banking employees working in a specific region. Therefore, future research could focus more on the influence of Covid-19 on the organizational culture of the banking system and provide insight into this direction of research.

This study provides directions for human resource management for developing effective practices for improving the performance of the employees in the banking sector.

This study offers support to the banking sector by providing insights into how it can improve the working environment and, thereby, enhance working in the banking sector.

This is the study that attempts to provide insights into how ergonomics is important for working in the banking sector, especially during a pandemic. The findings provide important implications for the banking sector and improve work ergonomics.

Start-ups are the new avenues for innovation and employment. Strategic management is critical for employee engagement and skill development of start-ups. This study aims to understand the impact of strategic management on employee engagement and skill development.

The study attempts to identify principal factors of strategic management influencing employee engagement and skill development. Structural equation modeling has been used to understand effects of the study.

The study results have shown the challenges concerning employee skill development and reflected on importance of the employee engagement programmes for the growth of the human resource in the start-ups.

The study has confined to strategic management for employee engagement and skill development. However, studies related to challenges encountered by start-ups in the specific areas of marketing, operations and finance, etc. would provide more detailed impact on the growth of start-ups.

This study provides an insight into strategic management for employee engagement and skill development. The results would provide directions for improving strategy management from the perspective of employee engagement and skill development.

The study on start-ups provides a direction to the owners of start-ups to understand the importance of strategic management and human resource management for building strong enterprising which can provide employment opportunity for the youth of the nation and improve the society at large.

This paper is an attempt to provide directions for managing challenges from the perspective of employees’ engagement and skill development, which is essential for growth and sustainability in the future.

Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the generation of the rules is quite high. On the other hand, the candidate rules generated using the traditional association rules mining face a huge challenge in terms of time and space, and the process is lengthy. In order to tackle the issues of the existing methods and to render the privacy rules, the paper proposes the grid-based privacy association rule mining.

The primary intention of the research is to design and develop a distributed elephant herding optimization (EHO) for grid-based privacy association rule mining from the database. The proposed method of rule generation is processed as two steps: in the first step, the rules are generated using apriori algorithm, which is the effective association rule mining algorithm. In general, the extraction of the association rules from the input database is based on confidence and support that is replaced with new terms, such as probability-based confidence and holo-entropy. Thus, in the proposed model, the extraction of the association rules is based on probability-based confidence and holo-entropy. In the second step, the generated rules are given to the grid-based privacy rule mining, which produces privacy-dependent rules based on a novel optimization algorithm and grid-based fitness. The novel optimization algorithm is developed by integrating the distributed concept in EHO algorithm.

The experimentation of the method using the databases taken from the Frequent Itemset Mining Dataset Repository to prove the effectiveness of the distributed grid-based privacy association rule mining includes the retail, chess, T10I4D100K and T40I10D100K databases. The proposed method outperformed the existing methods through offering a higher degree of privacy and utility, and moreover, it is noted that the distributed nature of the association rule mining facilitates the parallel processing and generates the privacy rules without much computational burden. The rate of hiding capacity, the rate of information preservation and rate of the false rules generated for the proposed method are found to be 0.4468, 0.4488 and 0.0654, respectively, which is better compared with the existing rule mining methods.

Data mining is performed in a distributed manner through the grids that subdivide the input data, and the rules are framed using the apriori-based association mining, which is the modification of the standard apriori with the holo-entropy and probability-based confidence replacing the support and confidence in the standard apriori algorithm. The mined rules do not assure the privacy, and hence, the grid-based privacy rules are employed that utilize the adaptive elephant herding optimization (AEHO) for generating the privacy rules. The AEHO inherits the adaptive nature in the standard EHO, which renders the global optimal solution.

The International Journal of Organizational Analysis (IJOA) is a leading journal that has published high-quality research focused on various facets of organizational analysis since 1993. This paper aims to conduct a retrospective analysis of the IJOA journey from 2005 to 2020.

The data used in this study was extracted using the Scopus database. The bibliometric analysis, using several indicators, is adopted to reveal the major trends and themes of the journal. The mapping of bibliographic data is carried using VOSviewer and Biblioshiny.

The study findings indicate that IJOA has grown for publications and citations since its inception. Five significant research directions emerged, i.e. organizational diagnostics, organization citizenship behaviour, organizational commitment to employee retention, psychological capital and firm performance, based on cluster analysis of IJOA’s publications.

To the best of the authors’ knowledge, this is the first study to conduct a comprehensive bibliometric analysis of IJOA. The study presents the key themes and trends emerging from a leading journal, considered a high-quality journal, for researching various facets of organizational functioning by academicians, scholars and practitioners.

The growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.

A portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.

The HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.

The framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.

The previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.

The purpose of this exploratory, empirical study is to gain insight into repatriation experiences and repatriate turnover intention of employees from India and The Netherlands who either were or had been on international assignments in the respective countries.

Interviews were conducted with 25 Dutch and 30 Indian international assignees (IAs) and repatriates in both India and The Netherlands. Thematic analysis resulted in four themes: met and unmet expectations of career advancement opportunities; knowledge transfer and labour marketability; economic growth versus economic recession and alternative employment opportunities; and boundaryless careers: adventure and entrepreneurship.

Repatriate expectations about the use of knowledge, skills and abilities gained in the host country moderate the relationship between the macro-economic situation of the home country and repatriate attrition/retention, such that met expectations of Indian respondents decreased their intention to leave the organisation, even in a conducive macro-economic context with ample alternative employment opportunities. Unmet expectations of Dutch respondents increased their intention to leave the organisation, even in an unfavourable macro-economic context with few alternative employment opportunities.

The sample of Indian and Dutch IAs and repatriates may limit generalisation of the findings to samples from other countries with distinct cultural contexts and macro-economic conditions.

Global organisations that set realistic expectations about re-entry career opportunities for repatriates, facilitate knowledge transfer after repatriation, and adequately respond to boundaryless career ambitions of repatriates, can reduce repatriate turnover intention and attrition.

This study shows that repatriate attrition versus retention is embedded in the macro-economic context of the home country, leading to three types of career mobility upon completion of an international assignment: intra-organisational mobility; organisational boundary-crossing; and geographical boundary crossing.