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This study has conducted exploratory research to understand who should comprise the members of a resilient supply chain for promoting an entrepreneurial ecosystem of a startup project and to determine the mechanisms for the balanced coexistence of all stakeholders. This is necessary to ensure mutual benefits for all stakeholders, each of whom has multidimensional interests. Additionally, this supply chain must be able to withstand any potential disruption risks.

This research has employed a mixed-design approach. In this context, the study conducted an extensive qualitative and quantitative investigation, including 30 interviews and a survey involving 180 potential stakeholders in this supply network, respectively in the capital city of Bangladesh, Dhaka. The analysis of the interviews utilized principles of matrix thinking, while structural equation modeling (SEM) through LISREL was employed to understand cause-and-effect relationships.

Network, platform and governance—these three independent constructs have the potential to contribute to the dependent construct, a resilient supply chain, aimed at promoting an entrepreneurial ecosystem for startup projects. It has been revealed that the management of such projects depends on the rules and regulations within the ecosystem. An excellent governance mechanism is essential for this purpose. To facilitate coexistence, the establishment of a platform is crucial, where cooperation among all members is mandatory.

For practitioners, three distinctive but closely interdependent issues are explored and resolved in this philanthropic study. It has unfolded the elements of any startup project with essential settings.

The identification of the structural dynamics of potential stakeholders within the entrepreneurial ecosystem of startups is largely absent in existing literature. Therefore, there is a need to comprehensively investigate the entire network, including their roles, responsibilities and associations. This study makes a significant and novel contribution to the existing literature. Academics and practitioners alike have ample opportunities to learn from this new aspect of relationships across three distinct areas: the entrepreneurial ecosystem, startup projects and the development of a resilient supply chain.

Despite the ongoing calls for the incorporation of the cloud utility model, the effect of the cloud on elements of supply chain performance is still an evolving area of research. The purpose of this paper is to develop the architecture of a cloud-based supply chain management (C-SCM) ecosystem and explore how it enhances supply chain responsiveness (SCR).

First, the authors discuss the potential benefits that cloud computing can yield, compared to existing mature SCM information systems and solutions through a comprehensive literature review. The authors conceptualise SCR in terms of the level of visibility in the supply chain, supply chain flexibility and rapid detection and reaction to changes, and then the authors build the detailed architecture of a C-SCM system. The proposed ecosystem introduces a view of SCM and the associated practices when transferred to cloud environments. The potential to enhance SCR through the cloud is explored with scenarios on a case of supply chain operations in fashion retail industry.

The findings show that the proposed system can enhance all three dimensions of SCR. Implications for supply chain practice and how companies can migrate to a cloud supply chain are drawn.

Given that the development, creation and delivery of goods and services are increasingly becoming a joint effort of several parties in a supply chain, the authors contribute to the existing literature by introducing a comprehensive C-SCM system and show how companies can enhance their SCR.

Decision support systems are becoming an indispensable tool for managing complex supply chains. The purpose of this paper is to develop a multi-agent-based supply chain management system that incorporates big data analytics that can exert autonomous corrective control actions. The effects of the system on supply chain agility are explored.

For the development of the architecture of the system, a sequential approach is adopted. First three fundamental dimensions of supply chain agility are identified – responsiveness, flexibility and speed. Then the organisational design of the system is developed. The roles for each of the agents within the framework are defined and the interactions among these agents are modelled.

Applications of the model are discussed, to show how the proposed model can potentially provide enhanced levels in each of the dimensions of supply chain agility.

The study shows how the multi-agent systems can assist to overcome the trade-off between supply chain agility and complexity of global supply chains. It also opens up a new research agenda for incorporation of big data and semantic web applications for the design of supply chain information systems.

The proposed information system provides integrated capabilities for production, supply chain event and disruption risk management under a collaborative basis.

A novel aspect in the design of multi-agent systems is introduced for inter-organisational processes, which incorporates semantic web information and a big data ontology in the agent society.

Given the growth of virtual reality (VR)-based tourism experiences in the past five years, this study aims to investigate the impact of VR-based interactions (ergonomics and embodiment) on memorable experiences and revisit intention mediated by cognitive and emotional responses.

This study has used an exploratory sequential mixed methodology research design to operationalise this research. Study 1 uses qualitative in-depth interviews to explore the proposed research questions, and Study 2 uses a 3 × 3 factorial experimental research design to test the proposed hypothetical model with 355 samples.

The results indicate that embodiment plays a more crucial role than VR ergonomics. Also, the cognitive response in the virtual tour indirectly generates a more memorable experience than the emotional response.

This research uses the theory of technological mediation as an overarching framework to conceptualise the research. Also, the research has applied the tenets of cognitive embodiment theory, metacognitive theory and other related theories to develop the arguments. Thus, the results of this research will extend the holistic understanding of these theories.

This research will guide VR tourism developers in understanding the requirements and expectations of tourists. It also serves as a manual to understand how tourists process the VR tour psychologically.

Very minimal focus was given to understanding the tourists’ interaction with technology in VR tours. The concept of ergonomics and embodiment investigated as an experimental variable is a novel approach in technology-based tourism research.

Fake news on social media about COVID-19 pandemic and its associated issues (e.g. lockdown) caused public panic that lead to supply chain (SC) disruptions, which eventually affect firm performance. The purpose of this study is to understand how social media fake news effects firm performance, and how to mitigate such effects.

Grounded on dynamic capability view (DCV), this study suggests that social media fake news effects firm performance via SC disruption (SCD) and SC resilience (SCR). Moreover, the relation between SCD and SCR is contingent upon SC learning (SCL) – a moderated mediation effect. To validate this complex model, the authors suggest effectiveness of using partial least squares structural equation modeling (PLS-SEM). Using an online survey, the results support the authors’ hypotheses.

The results suggest that social media fake news does not affect firm performance directly. However, the authors’ serial mediation test confirms that SCD and SCR sequentially mediate the relationship between social media fake news and firm performance. In addition, a moderated serial mediation test confirms that a higher level of SCL strengthens the SCD–SCR relationship.

This work offers a new theoretical and managerial perspective to understand the effect of fake news on firm performance, in the context of crises, e.g. COVID-19. In addition, this study offers the advancement of PLS as more robust for real-world applications and more advantageous when models are complex.

Prior studies in the SC and marketing domain suggest different effects of social media fake news on consumer behavior (e.g. panic buying) and SCD, respectively. This current study is a unique effort that investigates the ultimate effect of fake news on firm performance with complex causal relationships via SCD, SCR and SCL.

Deepfakes are fabricated content created by replacing an original image or video with someone else. Deepfakes have recently become commonplace in politics, posing serious challenges to democratic integrity. The advancement of AI-enabled technology and machine learning has made creating synthetic videos relatively easy. This study explores the role of political brand hate and individual moral consciousness in influencing electorates' intention to share political deepfake content.

The study creates and uses a fictional deepfake video to test the proposed model. Data are collected from N = 310 respondents in India and tested using partial least square–structural equation modelling (PLS-SEM) with SmartPLS v3.

The findings support that ideological incompatibility with the political party leads to political brand hate, positively affecting the electorates' intention to share political deepfake videos. This effect is partially mediated by users' reduced intention to verify political deepfake videos. In addition, it is observed that individual moral consciousness positively moderates the effect of political brand hate on the intention to share political deepfake videos. Intention to share political deepfake videos thus becomes a motive to seek revenge on the hated party, an expression of an individual's ideological hate and a means to preserve one's moral self-concept and strengthen their ideologies and moral beliefs.

The study expands the growing discussion about disseminating political deepfake videos using the theoretical lens of the negative consumer-brand relationship. It validates the effect of political brand hate on irrational behavior that is intended to cause harm to the hated party. Further, it provides a novel perspective that individual moral consciousness may fuel the haters' desire to engage in anti-branding behavior. Political ideological incompatibility reflects ethical reasons for brand hate. Therefore, hate among individuals with high moral consciousness serves to preserve their moral self.

The first research objective is to understand the role of digital [artificial intelligence (AI)] technologies on user engagement and conversion that has resulted in high online activities and increased online sales in current times in India. In addition, combined with changes such as social distancing and lockdown due to the COVID-19 pandemic, digital disruption has largely impacted the old ways of communication both at the individual and organizational levels, ultimately resulting in prominent social change. While interacting in the virtual world, this change is more noticeable. Therefore, the second research objective is to examine if a satisfying experience during online shopping leads to repurchase intention.

Using primary data collected from consumers in a developing economy (India), we tested the theoretical model to further extend the theoretical debate in consumer research.

This study empirically tests and further establishes that deploying AI technologies have a positive relationship with user engagement and conversion. Further, conversion leads to satisfying user experience. Finally, the relationship between satisfying user experience and repurchase intention is also found to be significant.

The uniqueness of this study is that it tests few key relationships related to user engagement during this uncertain period (COVID-19 pandemic) and examines the underlying mechanism which leads to increase in online sales.

The authors aim to investigate whether ability electronic human resource management (e-HRM) practices, opportunity enhancing e-HRM practices and motivation enhancing e-HRM can possibly lead to development of sustainable e-HRM systems. Finally, the authors also examined if sustainable e-HRM systems can enhance firm performance.

The model was developed using dynamic capability view perspective. The study tests theoretical model and presents findings by analysing data (partial least squares structural equation modelling method) gathered from 151 South African firms.

The findings indicate that ability enhancing e-HRM practices and motivation enhancing e-HRM practices can result in development of sustainable e-HRM systems, and findings also indicate that sustainable e-HRM systems can improve firm performance.

Emphasis is required on ability enhancing e-HRM practices and motivation enhancing e-HRM practices to develop sustainable e-HRM systems. Once workforce understand the complete benefits of e-HRM, they will start using this system on a regular basis for activities including goal setting, and performance measurement. The development of sustainable e-HRM systems will improve firm performance especially from cost control and customer satisfaction perspective.

This study advances the conceptual debate in the e-HRM domain through the development and testing of theoretical model.

The purpose of this paper is to develop an analytical model for assessing the performance of supplier relationships (SRs). The majority of performance measurement models incorporate hard quantitative measures that are not appropriate for the soft features of business relationships. As they are usually designed by the customer organisation, they are imposed on suppliers, they do not take into account the relationship as a unit of analysis and therefore they carry a bias in their interpretation.

For the development of the model, the nature of a SR is conceptualised in terms of two typologies: one based on the level of its analysis and one based on its genesis and development and the methodology of gap analysis is used.

The performance of SRs is assessed in terms of several disparities that exist between the participating parties' perceptions of the nature and their performance to the relationship as well as their perception of their partners' performance to the relationship. The proposed model can be utilised with qualitative (interviews) as well as quantitative (survey) data. The aim of any improvement strategy for the performance of SRs should be to minimise the gaps in partners' perceptions and pursuit the role that the parties play in the relationship and identify those factors that have greater importance to the relationship. Appropriate strategies should be then selected to minimise the gaps in the perceptions of the individuals against these factors.

The usefulness of the model in assessing SRs' performance lies in the fact that a holistic view of SRs is achieved by taking into account both soft and hard dimensions of SRs. Contrasting the model to other performance management models its major limitation is that it cannot be used as a “scientific” diagnostic tool for suggestion of best practices. Further research is required to identify the causes behind poor performance in a particular area and then devise appropriate strategies.

The proposed model can be used in different context (manufacturing or services), does not require specialised knowledge or external consulting and provides scope for improvement of relationships between departments within an organisation.

This paper emphasises the importance of performance measurement of SRs and proposes an innovative for performance measurement model, which overcomes the limitations of existing tools and can be applied in several contexts.