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Currently, the Covid-19 pandemic is changing how consumers shop, encouraging deeper levels and increased reliance on e-commerce systems and social media such as online communities. The online interaction of consumers is more important and brings many uncertainties, which impact the original commerce environment. This study aim to investigate the ethical consideration of information credibility and perceived privacy risk from a psychology perspective in marketing, this study draws on social support theory from social psychology to develop a research model to investigate the role of information credibility and perceived privacy risk on social commerce websites.

This study investigated social commerce websites and communities. The research data of this study was collected through a questionnaire from consumers on three famous social commerce platforms. Using PLS-SEM to perform data analysis, this study research the importance of information credibility, perceived privacy risk and trust on social commerce websites.

The findings discuss individuals' reaction to privacy issues and to understand the motives to disclose or reveal personal information within a marketing or consumption context. The research also explores the theoretical implications by integrating theories from information systems and social psychology to investigate ethical issues in social commerce.

Covid-19 makes peer-to-peer communication in online communities is developing collaborative consumption, and information produced in these communities can influence the decisions of consumers. Covid-19 has exacerbated such a change in social commerce environment. Therefore, information credibility plays an important role in developing online communities. It is important to look at the psychological antecedents that drive consumers' willingness to share their personal information when using online communities. The author has clarified which aspects of trust in social commerce should be strategized, including information trustworthiness, perceived privacy risks, social support and information sharing. These are the details that companies should pay more attention to when operating social commerce. Only by paying more attention to these details and giving consumers a positive feeling can consumers' trust be maintained or enhanced, ultimately leading to a successful trust economy.

This paper uses the Technology Acceptance Model (TAM) to assess the readiness of the HR function within the UK Civil Service (CSHR) to implement AI to support performance. Academic literature in relation to AI acceptance in HR functions is currently limited, so this paper aims to establish a better understanding of the current landscape and level of ambition in this area.

A quantitative research approach was adopted to determine likely behavioral intentions of workers in the human resource (HR)function if AI were implemented, by investigating key aspects of the TAM (the perceived usefulness of AI and the transparency of the CSHR in adopting AI).

While the results suggest that the CSHR is not ready to harness AI opportunities, employees were personally ready, despite perceiving a lack of sufficient knowledge in this area. The paper identifies that more time needs to be spent on raising awareness and upskilling the HR function before the CS can be considered fully ready to harness these opportunities.

The penetration of artificial intelligence (AI) technologies into the global workforce brings transformative potential to the governance structures and use of digital platforms in public sector organizations. AI is likely to play a role in the operation of HR functions and influence how they might operate in the near future.

The recent proliferation of social media platforms has witnessed a growth in social commerce by using social media to facilitate interactivity between customers and vendors. While emergent studies on social commerce are growing, their focus tends to be on millennials and cross-age groups. Given the growth of digital natives in shaping the online shopping experience of the future, we deemed an application to Generation Z necessary and overdue.

We draw on the existing literature and develop a framework to understand social commerce dynamics for digital natives. We employ PLS and CB-SEM to test our proposed model.

Our findings demonstrate the importance of social commerce information sharing activities in facilitating social support, a sense of warmth and belongingness, and online trust for Generation Z platform users. We also investigate the roles of online trust and perceived risk on intention to purchase and find support for both relationships. Finally, we discuss the findings in terms of theoretical and managerial contributions and conclude the study with limitations and future research directions.

This research is unique by using social commerce theory to explore Gen Z platform users. The finding will contribute to information system literature by expanding the social commerce research stream.

The advantages of applying big data analytics for organizations to boost innovation performance are enormous. By collecting and analysing substantial amounts of data, firms can discern what works for their customer needs and update existing products while innovating new ones. Notwithstanding the evidence about the effects of big data analytics, the link between big data analytics and innovation performance is still underestimated. Especially in today's fast-changing and complicated environments, companies cannot simply take big data analytics as one innovative technical tool without fully understanding how to deploy it effectively.

This study tries to investigate this relationship by building on the knowledge absorptive capacity perspective. The authors conceptualized effective use of big data analytics tools as one general absorptive capacity rather than a simple technical element or skill. Specifically, effectively utilize big data analytics tools can provide values and insights for new product innovation performance in a turbulent environment. Using online survey data from 108 managers, the authors assessed their hypotheses by applying the structural equation modelling method.

The authors found that big data analytics capacity, which can be conceptualized as one absorptive capacity, can positively influence product innovation performance. The authors also found that environmental turbulence has strong moderation effects on these two main relationships.

These results establish big data analytics can be regarded as one absorptive capacity, which can positively boost an organization's innovation performance.

Consumers may enjoy the information sharing and social support made available when a social media platform is used for pre-purchase research; however, do consumers reevaluate the privacy and security of the platform differently when ordering and payment capabilities are added? As social media systems have evolved into social commerce platforms (SCPs), individuals are often faced with whether to complete a purchase they have been researching or switch to a traditional e-commerce platform to complete the transaction. This research examines consumer trust formation in the SCP channel and how consumer interest and engagement in the channel are maintained and influence consumer decisions to purchase via the SCP.

Based on trust and involvement literature, a research model was conceptualized to capture consumer beliefs about SCP privacy and security and whether the SCP can be trusted, using these inputs into subsequent consumer interest, engagement and decisions on whether to use the SCP for purchasing. The research model was empirically tested using the panel data's structural equation modeling (AMOS) (n = 405). The data showed acceptable reliability and convergent validity, while the original research model provides predictive validity and theory-confirming insights.

Results confirm that consumer perceptions of privacy and security play a crucial role as decision criteria, informing their judgments of whether a new social commerce channel can be trusted enough to conduct purchases. Further, consumer trust supports their interest in the SCP, resulting in enduring and enhanced behavioral use and, to a lesser extent, purchase intent. Still, a majority of this sample declined to purchase using the SCP and rather preferred to transact on tried and trusted traditional e-commerce sites.

This study is among the first to examine trust formation in new SCPs, where consumers are deciding to expand their engagement level from social and informational to commercial.

Given the growing importance and demand for online food purchases, this study explores the new advancements in information and communication technologies (ICTs) by examining the key features of social commerce, trust and product’s attributes in the e-commerce environment. The aim is to investigate possible ICTs-related entrepreneurial opportunities in the food and beverage (F&B) industry.

The study uses a survey to collect data and applies Smart partial least squares to test the model.

The structural equation modelling results illustrated that social commerce constructs significantly impact trust, leading to customer’s purchase intention. Additionally, product’s attributes was found to have a significant relationship with customer’s purchase intention with trust being the most pertinent driver.

This study contributes to the F&B literature by highlighting the role of new forms of technologies in entrepreneurship activities, especially for small and medium-sized enterprises.

This study investigates the relationship between buyers’ psychological antecedent and repurchase intentions in online group buying. Considering and evaluating pre-purchase, the authors measure the buyers’ overall experience of online group buying through their perceived value (PV) and risk. This study examines the influence of PV and perceived risk (PR) on positive electronic word-of-mouth (eWoM) communication and repurchase intention in online group buying.

The authors verify the research model using SPSS and the structural equation modeling-partial least square (SEM-PLS) to analyze 839 convincing respondents. This quantitative research provides insights into online group buying, including the food industry.

The results demonstrate that the buyers’ PV of online group buying enhanced positive eWoM communication and repurchase intention. The willingness of buyers to spread positive eWoM indicates their recognition and satisfaction with a product or brand. Thus, they have the behavioral intention to repurchase in online group buying. The study found that while positive eWoM communication significantly impacts repurchase intention, PR negatively affects PV. The research provides theoretical and practical implications at the end of the study.

This study has some limitations. First, the study only used PV and PR to measure consumers’ considerations and evaluations of the initial stage in the consumer decision journey. Future studies can include more dimensions that may further affect these considerations and assessments to verify the research model. Second, the study only used positive eWoM communication to measure the “enjoy-advocate-bond” of consumption and usage in the post-purchase stage.

The study proposes the sequential relationship in the psychological decision procedure of participating in online group buying and provides valuable managerial implications for managers operating online group buying on third-party platforms. The findings provide good knowledge for the food industry to stay connected with customers and develop their satisfaction.

In this study, the authors examine how organizational-, systems- and interpersonal-level trust may be required for a smooth functioning of the firms in the sharing economy (SE). The research objective is to explore the trust-building mechanisms of Airbnb, a leading SE organization, and its aim to foster generalized trust. An investigation of the Airbnb's promotion of different trust-building mechanisms will allow to evaluate their effectiveness in how they can help overcome scepticism and distrust between the transacting parties. Consequently, the authors can develop a unique theoretical perspective on generalized trust in SE environments and better understand any trust-related barriers preventing SE transactions.

The authors employ a case study approach to investigate the research questions with the aim to fully understand the abstract and complex nature of trust. They focus on Airbnb as the company enjoys a leading market position, being a sharing economy firm. Moreover, the personal nature of accommodation sharing, which is the business of Airbnb, increases users' trust requirements, and so the company must take active steps to promote trust between the transacting parties. The authors adopt thematic analysis to execute the data analysis of the study's findings, which are derived from emergent themes and directed by the research objectives and relevant literature.

The results show that users of Airbnb are concerned about the danger of opportunistic hosts, although they are primarily motivated to use the company's services due to its economic benefits. Nevertheless, the success of Airbnb platform stems from the trust that the company has succeeded in establishing among its users, in particular interpersonal trust. Analysis reveals that generalized trust is fostered at an interpersonal level in the form of peer reviews, at an organizational level in terms of brand familiarity and at a systems level in regards to interface design.

The authors advance the argument that confidence to transact in the social economy stems from a combination of three levels of trust, including organizational-, systems- and interpersonal-level trust. These findings contribute to the body of trust research in information technology and people literature from its unique investigative setting, whilst simultaneously strengthening the primarily speculative research on SE with in-depth empirical evidence.

Innovative firms leverage big data analytics (BDA) benefits in optimising value creation, particularly in business-to-business (B2B) contexts. Examples of this are found in new product success and product innovation performance. However, knowledge of how innovative firms and their corporate customers generate insights from big data, develop new products and gain higher-quality service from intra- and inter organisations' resources is limited. This knowledge manifests in the form of opportunities available in BDA and through the adoption of the co-creation approach to generate value in the form of new product innovation. BDA reflects an excellent means of enhancing a firm's customer agility, but how this is possible remains largely unknown.

In this research, the authors hypothesise that new product success is a function of a firm's customer agility and product innovation performance moderated by environmental turbulences. In turn, the firm's customer agility is enhanced by the effect of big data aggregation and analytical tools. These hypotheses have been confirmed by a survey in an emerging market.

The authors use structural equation modelling to test the authors’ hypotheses. The main contribution of this research is the conceptualisation and test of an integrative framework identifying the links among a firm's customer agility, new product success and BDA capabilities.

The study established that BDA tools – the effective use of data aggregation tools and the effective use of data analysis tools – shape customer agility in achieving new product success. This study contributes to one’s understanding of the relevance of BDA in B2B value creation contexts.

The study findings show that BDA shapes a firm's customer agility in achieving new product success.

This study examines the impact of social media information sharing and usage on consumer beliefs particularly in the credibility of the information provided by e-commerce vendors, and consumer trust formation.

Drawing on trust through social media usage and surface credibility, the authors have proposed a research model to investigate consumers satisfaction on food and beverage (F&B) products. Empirical support for the research model was provided by using structural equation modelling using survey data drawn from Malaysian consumers with an account with Facebook.

Results indicate that consumer participation in social media communities support higher levels of consumer trust and ratings of the surface credibility of information provided by an F&B vendor, and surface credibility also helped to develop consumer trust. Trust in the vendor also exerted a positive influence on consumer satisfaction with F&B product offerings. Results suggest that F&B that provide credible and transparent information regarding their branded products, enjoy increased levels of consumer trust, leading to higher levels of consumer satisfaction with their F&B consumption experience.

The result of this research contributes to social commerce branch of literature and has practical implications for practitioners in the F&B industry as a means to survival strategies to embrace critical and challenging period during an endemic, particularly. As such, this study analyses the relationship between social media usage, surface credibility, trust and satisfaction for developing consumer trust while managing enterprise social media.