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This study aims to determine website quality, young adult socialization and dark triad personality as the factors influencing the real estate purchase decision. In addition, this study also measures the mediating effects of young adult socialization on real estate purchase buying behavior.

Related literature, quantifiable variables with a five-point Likert scale, hypothesis testing and mediators are used to study the model. A systematic questionnaire that was divided into four sections was used. A total of 336 valid responses were collected and analyzed through a structural equation model.

The results suggest that dark triad personality and young adult socialization considerably affect real estate purchase decisions. The development proves website quality does not significantly impact real estate purchase behavior.

This study is limited to a few young consumers’ responses. Future studies could be more widespread globally and should include more variables and offline methods of purchasing behavior.

As per the review of existing literature, this research is the first, to the best of the authors’ knowledge, to determine the factors affecting the real estate purchase decision with factors like website quality, dark triad personalities and young adult socialization involving it.

Using dynamic capabilities (DCs) theory, the authors assess whether micro, small and medium-sized enterprises (MSMEs) can leverage DCs to improve operational capabilities (OCs) during the COVID-19 pandemic. The authors also identify whether organizational learning (OL) affects the relationship between DCs and OCs.

The authors test these propositions on a sample of 419 MSMEs from Australia and New Zealand.

DCs have no direct effect on OCs, technological or marketing capabilities (TCs or MCs). OL moderates the effect of DCs on both TCs and MCs.

The study assesses only MCs and TCs as OCs and does not explicitly measure pandemic impacts on organizations. However, the results illustrate the importance of OL during crises for recovery purposes.

Managers can use the findings to improve structure, processes and knowledge management emanating from MCs and TCs within organizations impacted by the COVID-19 pandemic.

The authors use a multi-dimensional measure of OL and show that during the pandemic, OL is a critical factor that allows organizations to transform the benefits conferred by DCs into MCs and TCs.

This study mainly aims to explore the causal nexus between big data-driven organizational capabilities (BDDOC) and supply chain innovation capabilities (SCIC) and innovation performance (IP), then explore the indirect effect of SCIC and also test the moderating effects for both internal supply chain integration (ISCI) and external supply chain integration (ESCI) into the relationship between BDDOC and SCIC.

In order to test the conceptual model and the hypothesized relationships between all the constructs, the data were collected using a self-reported questionnaire by workers in Jordanian small and medium manufacturing enterprises. Partial least squares-structural equation modeling (PLS-SEM) was employed to test the model.

The paper reached a set of interesting results where it was confirmed that there is a positive and statistically significant relationship between BDDOC, SCIC and IP in addition to confirming the indirect effect of SCIC between BDDOC and IP. The results also showed that there is a moderating role for both ESCI and ISCI.

This study can be considered the first study in the current literature that investigates these constructs as shown in the research model. Therefore, the paper presents an interesting set of theoretical and managerial contributions that may contribute to covering part of the research gap in the literature.

At the forefront of current research is the investigation of how big data analytics capability (BDAC) and artificial intelligence capability (AIC) can enhance performance in concert. Therefore, current study intended to conduct more deep research into emerging phenomena and attempts to cover the gap by exploring how entrepreneurial orientations (EO) emphasize the use of two emerging capabilities under the moderating role of environmental dynamism which in turn augment co-innovation and hotel performance.

Data were collected from four-star and five-star hotels located in Kula Lumpur and Langkawi in Malaysia. A total of 260 responses were obtained from IT staff and senior managers with the assistance of a Manpower agency for data analysis. The hypotheses were examined by analyzing the data using PLS-SEM technique through Smart PLS 3 software.

The result revealed that EO has a positive and significant effect on co-innovation (CIN). Additionally, the BDAC and AIC have been tested and proven to be potential mediators between EO and CIN. Also, environmental dynamism as moderator has positive and significant effect on BDAC and co-innovation performance, however, not significant impact on AIC and co-innovation performance. Lastly, findings displayed positive and significant moderated mediation impact of environmental dynamics on BDAC and CIN with hotel performance, but not significant influence on AIC and co-innovation with hotel performance. For theoretical corroboration of the research findings, the current study integrated EO, resource-based view theory and contingent dynamic capabilities (CDC), because neither single stance can explicate an extant research framework.

This study anticipated the several implications for the entrepreneurs of hospitality industry. Managers are recommended to invest in the entrepreneurial traits of the employees/organizations and make strategic readjustment of their capabilities for sustained business performance.

The study goes beyond the normal inquiry by investigating moderated mediation impact of environmental dynamism between two emerging capabilities, co-innovation and hotel performance relationships. Another novelty of this study is to culminate the exploitation and adoption of emerging IT-based capabilities in cross domains of management, entrepreneurship, information systems management within the hotel industry.

The objective of this research is to evaluate and rank the factors influencing omnichannel (OC) logistics, while also investigating the significant impact of big data analytics in improving these drivers of OC logistics.

Using exploratory sequential mixed method design, an in-person interview survey was conducted to identify and stratifies the enablers of OC retailing. These interviews were supplemented with a case study in an apparel firm to prioritise the enablers of OC logistics. Further, a survey was conducted to understand the role of big data analytics in improving drivers of OC logistics as well as the role of Individual capability and organisational capability in big data usage for omnichannel retailing.

Findings represent that information management is the most important driver followed by inventory management and network design for improving OC logistics. Further, significant relationship between big data analytics and drivers of omnichannel logistics has been reported.

This study identifies and classifies the drivers of OC retailing relating to their level of criticality in OC logistics which will assists practitioners to prioritise their tasks for the successful development of OC logistics. The study will also help practitioners to use BDA for developing the drivers of OC.

The study substantiates and adds to the BDA literature by emphasising the positive role of BDA in development of OC driver and highlighting the significant role of drivers of BDA in its usage.