Search results

Today, companies are struggling to develop their human resources analytics (HRA) capability, although interest in the subject is rapidly increasing. Furthermore, the academic literature on the subject is immature with limited practical guidance or comprehensive models that could support organisations in the development of their HRA capability. To address this issue, the aim of this paper is to provide a maturity model – i.e. HRAMM – and an interdependency matrix through which an organisation can (1) operationalise its HRA capability and assess its organisational maturity; (2) generate harmonious development roadmaps to improve its HRA capability; and (3) enable benchmarking and continuous improvement.

The research described in this paper is based on the popular methodology proposed by Becker et al. (2009) and the procedure for maturity evaluation developed by Gastaldi et al. (2018). This method combines academic rigour and field experience in analytics, in a process spanning eight main phases that involves literature reviews and knowledge creation techniques.

We define HRA maturity through four areas and 14 dimensions, providing a comprehensive model to operationalise HRA capability. Additionally, we argue that HRA maturity develops through an evolutionary path described in four discrete stages of maturity that go beyond traditional analytics sophistication. Lastly, the interdependency matrix reveals specific enablers for the development of HRA.

This paper provides practitioners with useful tools to monitor, evaluate and plan their HRA development path. Additionally, our research helps practitioners to prioritise their work and investment, generating an effective roadmap for developing and improving their HRA capability.

To the best of the authors’ knowledge, this study is the first to provide a model for evaluating the maturity of HRA capability plus an interdependency matrix to evaluate systematically the prerequisites and synergies among its constituting dimensions.

In the present article, sensitivity analysis was studied in the presence of the combined effects of thermal radiation, suction and magnetohydrodynamics (MHD) effects on a Nimonic 80A-Fe_3O4/water hybrid nanofluid across moving a wedge with variable surface temperature and buoyancy effects.

The governing equations were transformed using similarity transformations and solved using MATLAB bvp4c code and response surface methodology (RSM), with quadratic face-centred central composite design being implemented. All results and graphs were formulated after positive outcomes of our results with existing literature.

An increase in magnetic parameter (M) and velocity ratio parameter (R) resulted in an increase in velocity profiles and local Nusselt number, while a reverse trend was observed for temperature profiles. With radiation parameter Rd = 0.8, the local Nusselt number increased by 4.08% as the velocity ratio parameter increased from R = 0.0 to R = 0.5. The Nusselt number was found to be most sensitive to R, while the latter produced negative sensitivity on skin friction coefficient. The skin friction coefficient for the hybrid nanofluid model increased by 35.39% compared to the regular fluid model, with a very low standard deviation value of 10⁻⁴. The Model F-value for Nusselt number model was found to be 939278.49 with a noise ratio of 3618.711. Skin friction coefficient was found to be most sensitive with respect to changes in the parametric values of M.

Nimonic 80A being a super-alloy of nickel-iron-chromium and built in high frequency melting, it can work up to 1500°F and is extensively used in automobile exhaust valves.

The present study finds numerous applications in biotoxicity studies, medical industries, water heaters and the forging of hot exhaust valve heads.

In view of various applications of our present study, there remains a gap in examining the sensitivity analysis of a hybrid nanofluid flow model across a moving permeable wedge using the Tiwari–Das model, which required clinical investigations numerically and statistically.

This study aims to provide a new perspective on the factors determining a country’s tourism performance, understand the interrelationships among these factors and explore their implications for the future of tourism in high-income countries.

The study employs a fuzzy-set qualitative comparative analysis (fsQCA) using five variables from the World Economic Forum’s Travel and Tourism Development Index (TTDI). The focus is on identifying seven configurations of antecedents of Travel and Tourism Industry Gross Domestic Product (T&T Industry GDP).

The study identifies seven configurations of antecedents influencing T&T Industry GDP, revealing how these factors operate in different scenarios, specifically in countries with high and low T&T GDP. These configurations offer insights into potential future pathways for tourism development.

The study implies that tourism is a complex phenomenon influenced by multiple interacting factors. It provides a framework for understanding how different combinations of factors can lead to high or low tourism performance, offering valuable insights for anticipating and shaping the future of tourism.

This study adds value by providing a more nuanced understanding of the tourism industry, challenging the notion of singular effects of variables and highlighting the importance of analyzing multiple, interacting factors in understanding and predicting tourism performance. It contributes to the field of futures studies by offering a tool for anticipating potential future scenarios and their impact on the tourism industry.

Despite the growing interest in blockchain technology (BCT) applications in the agri-food industry, evidence of their economic and strategic implications remains scarce. This study aims to contribute to filling this gap by jointly investigating how BCT adoption affects transactional relationships, and how it contributes to the firm’s strategic resources.

An explanatory case study is conducted based on a theoretical framework grounded on transaction cost economics and the resource-based-dynamic capabilities view. Six BCT implementations by agri-food firms are studied. Data were collected through semi-structured interviews and analysed using thematic analysis.

Findings reveal that BCT benefits depend on how companies integrate technology across their supply chains. In fact, the results suggest that overall transaction efficiency within the supply chain is enhanced only for those firms prioritising stakeholder engagement during technology implementation and leveraging existing trust relationships with economic agents. Moreover, the results suggest that BCT is not yet perceived as a strategic resource, but rather that it has the potential to enhance firms’ operational-adaptive, absorptive and innovative capabilities. When all supply chain actors clearly understand blockchain’s functionality and value, the development of these capabilities becomes more pronounced.

The study identifies two BCT adoption configurations. One primarily focuses on enhancing supply chain efficiency and transparency (dynamic BCT), while the other uses BCT mainly for marketing purposes (static BCT). These configurations lead to varied possibilities for leveraging BCT’s potential advantages. Furthermore, they show how a mismatch between a strategic approach and its chosen configuration could work against any positive impact and lead to disillusionment with the BCT. Thus, managers should assess carefully the impact of such different configuration choices on performance.

To the best of the authors’ knowledge, this is the first study to attempt to analyse the economic implications of adopting BCT in the food sector from both a firm and supply chain perspective. Additionally, it shows how interpreting these impacts is contingent on the diverse modalities for embedding BCT into existing supply chains.

With digitisation, a new kind of inequality has emerged in society between people and groups of people. A lack of digital inclusion creates challenges for the economic and social development of society and citizen participation. This study analyses how the country-level cultural factors defined by Hofstede are associated with citizens' digital skills and internet usage and how they moderate the effects of age, gender, educational level and income level.

This comparative cross-sectional study examines digital inclusion in 22 European countries. Data from the European Social Survey (N = 37,602) are analysed using a two-level regression analysis.

The study found significant effects of demographic and socio-economic factors and country-level indulgence on digital skills and internet usage. In addition, the study shows that a high value on the indulgence index moderates the negative effect of age.

The digital divide has been studied widely with regard to individual-level influencing factors and international comparisons. The significance of Hofstede’s cultural dimensions in terms of digitisation and digital divides has also been confirmed in previous studies. However, there is a lack of analysis combining the effects of country-level culture and individual-level demographic and socio-economic factors on citizens' digital skills and internet usage. Generally, the research emphasises the significance of national culture in digital inclusion and especially in supporting the digital inclusion of older adults.

The Metaverse and Internet of Things (IoT) have emerged like a tidal wave, and it is creating a transformative impact on society and industry. The metaverse and IoT changed the way companies were operating earlier and customers were living their lives. On the other hand, Metaverse enriches the customer experience by offering a matchless virtual experience using augmented reality and state-of-the-art technology. The metaverse and the IoT can be used in various sectors such as manufacturing, transportation, retailing, health care, banking, and automobiles to make cities smart. Metaverse and IoT provide real-time data, reduces operational cost and errors, improves efficiency, and helps industries to make intelligent decisions. Although the IoT and Metaverse offer significant benefits, it is not free from limitations. Ethical dilemmas, privacy issues, data breaches, and difficulty in extracting relevant data impose serious challenges that need to be addressed. There is an urgent and dire need to create a trade-off between the interest of the business and the privacy and security of customers. This chapter aims to discover the potential of Metaverse and IoT in various sectors (e.g., healthcare, transportation, and electronics). This study will bring significant insights to researchers and policymakers by exploring the likely benefits of IoT and metaverse in diverse sectors to develop smart cities. This chapter will also explain the challenges of metaverse and IoT, which can be addressed by integrating data analytics tools optimally and efficiently.

Environmental threats are becoming severe in developing and undeveloped countries. It urges to know how green banking operations can foster sustainable development in these regions. This study aims to provide empirical evidence of the determinants of green banking operations in Bangladesh.

Based on the socially responsible investing (SRI) theory, this study examined the hypothesized relationships using a partial least square structural equation modeling (PLS-SEM) approach. The Bayesian SEM (BSEM) through a Markov Chain Monte Carlo (MCMC) approach was also used to validate the study's first-order model.

The findings show that sustainable innovativeness, green investment and green banking policy substantially and positively change green banking operations. Notably, green investment is the most influential predictor of green banking operations, driving banks to establish sustainable economic systems within the country.

The findings offer valuable guidance for scholars, financial institutions, policymakers and bank managers to develop and implement effective strategies for green banking operations. These strategies may significantly contribute to achieving the sustainable development goals (SDGs) in Bangladesh.

This study is ground-breaking in associating sustainable innovativeness and green banking operations from a developing country. It enriches our understanding of green banking, aligning with existing literature. Additionally, PLS-SEM and BSEM provide strong validation of the proposed theoretical model.

The purpose of this paper is to study current practices in adopting blockchain technology amongst export companies in West Sweden and to capture their CEOs’ knowledge of and attitudes towards blockchains.

Factors enabling or hindering the adoption of blockchains were identified from a comprehensive literature review and a survey of 72 chief executive officers (CEOs) of export-oriented firms in West Sweden, all with turnovers exceeding €2m, regarding their knowledge of and attitudes towards blockchains.

Blockchain technology is not currently perceived to provide benefits that would outweigh the costs of introducing it into West Sweden’s export firms. Nevertheless, the findings suggest that such technology, though currently too immature to meet today’s industrial requirements, could experience more widespread use if certain key factors (i.e. lower cost, traceability, improved security or trustworthiness and new blockchain-enabled business models) are prioritised.

Answered by 72 CEOs, the survey achieved a response rate of 6%, meaning that the findings are only exploratory. Even so, they offer new insights into CEOs’ attitudes towards blockchain technology.

The CEOs reported comparatively limited knowledge of and experience with implementing blockchains, the lack of which has hampered their large-scale implementation in multi-actor supply chains.

Negative sentiment amongst CEOs towards blockchain technology may lower on-the-job satisfaction amongst tech personnel aspiring to develop and implement blockchain applications in their firms.

Knowledge of and attitudes towards blockchain technology amongst top-level managers, as well as about factors enabling or hindering its adoption, guide managers in crafting strategies for implementing blockchains in their organisations and maximising the benefits therein. Unlike past studies focussing on technological aspects or views of experts and middle-management, the study was designed to capture the views of CEOs.

The proliferation of non-fungible token (NFT)-based crypto-art platforms has transformed how creators manage, own and earn money through the creation, assets and identity of their digital works. Despite this, no studies have examined the drivers of continuous content contribution behavior (CCCB) toward NFTs. Hence, this study draws on the theory of relational bonds to examine how various relational bonds affect feelings of psychological ownership, which, in turn, affects CCCB on metaverse platforms.

Using structural equation modeling and importance-performance matrix analysis, an online survey of 434 content creators from prominent NFT platforms empirically validated the research hypotheses.

Financial, structural, and social bonds positively affect psychological ownership, which in turn encourages CCCBs. The results of the importance-performance matrix analysis reveal that male content creators prioritized virtual reputation and social enhancement, whereas female content creators prioritized personalization and monetary gains.

We examine Web 3.0 and the NFT creators’ network that characterizes the governance practices of the metaverse. Consequently, the findings facilitate a better understanding of creator economy and meta-verse commerce.

Migrants have been posed with less familiarity in their new environment during COVID times, faced with various social, psychological and emotional traumas. Research indicates that they may have been originating from apprehension of being abandoned by their neighbours. Most of them were precarious with little wages, competing for their basic need fulfilment, putting them under more mental stress. Looking forward to the ancient principle, ‘Athithi Devo Bhavah’ (Visitors are Gods), and immediate response, measures were taken to promote community shelters and kitchens, maintaining social distancing and ensuring physical safety. The governments of different countries took proactive initiatives to study and assess their needs. The study here includes the cases being evaluated regarding migrants' need for surveillance and psycho-social support given by the government and non-profit associations during the pandemic at the global level. Remarkably, certain countries proved the working of their sustainable poverty reduction model by evaluating various factors. The study started by introducing who migrants were, diagnosing their problems faced during the pandemic, how Sustainable Development Goals can be implemented and various measures taken at government and institutional levels to protect the migrant workforce.