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Knowledge management (KM) is an important topic in the age of big data, and this study adds to the existing body of literature by providing a novel KM perspective on the technological phenomenon of artificial intelligence (AI). This study aims to discover how AI might facilitate knowledge-based business-to-business (B2B) marketing. In this chapter, the authors take a close look at the building blocks of AI and the relationships between them. Future research directions and also the effects of the various market information building components on B2B marketing are discussed. The study’s approach is theoretical; it tries to provide a framework for characterising the phenomenon of AI and its constituent parts. Additionally, this chapter provides a methodical analysis of the three categories of market information crucial to B2B marketing: knowledge of customers, knowledge of users, and knowledge of external markets. This research looks at AI through the lens of the conventional data processing framework, analysing the six pillars upon which AI systems are founded. It also explained how the framework’s components work together to transform data into actionable information. In this chapter, the authors will look at how AI works and how it can benefit B2B knowledge-based marketing. It’s not aimed at AI experts but rather at general marketing managers. In this chapter, the possible effects of AI on B2B marketing are discussed using examples from the real world.

This paper extends the authors’ previous research work investigating resilience for municipal infrastructure from an asset management perspective. Therefore, this paper aims to formulate a pavement resilience index while incorporating asset management and the associated resilience indicators from the authors’ previous research work.

This paper introduces a set of holistic-based key indicators that reflect municipal infrastructure resiliency. Thenceforth, the indicators were integrated using the weighted sum mean method to form the proposed resilience index. Resilience indicators weights were determined using principal components analysis (PCA) via IBM SPSS®. The developed framework for the PCA was built based on an optimization model output to generate the required weights for the desired resilience index. The output optimization data were adjusted using the standardization method before performing PCA.

This paper offers a mathematical approach to generating a resilience index for municipal infrastructure. The statistical tests conducted throughout the study showed a high significance level. Therefore, using PCA was proper for the resilience indicators data. The proposed framework is beneficial for asset management experts, where introducing the proposed index will provide ease of use to decision-makers regarding pavement network maintenance planning.

The resilience indicators used need to be updated beyond what is mentioned in this paper to include asset redundancy and structural asset capacity. Using clustering as a validation tool is an excellent opportunity for other researchers to examine the resilience index for each pavement corridor individually pertaining to the resulting clusters.

This paper provides a unique example of integrating resilience and asset management concepts and serves as a vital step toward a comprehensive integration approach between the two concepts. The used PCA framework offers dynamic resilience indicators weights and, therefore, a dynamic resilience index. Resiliency is a dynamic feature for infrastructure systems. It differs during their life cycle with the change in maintenance and rehabilitation plans, systems retrofit and the occurring disruptive events throughout their life cycle. Therefore, the PCA technique was the preferred method used where it is data-based oriented and eliminates the subjectivity while driving indicators weights.

There is limited research examining the relationship between social media and green food purchasing behaviour. In the current study, we examine the factors that affect consumers’ green food purchasing behaviour in Türkiye.

Data collected from the participants by survey method were analysed using Smart PLS 4.0 with IBM SPSS 26 and PLS to run SEM.

Our findings have revealed that from all the structural elements in the theory of planned behaviour (TPB), only attitude and perceived behavioural control contribute to consumers’ green food purchasing behaviour, while subjective norms do not contribute to consumers’ green food purchasing behaviour. Additionally, it was found that social media usage (SMU) and digital marketing interactions (DMI) have a positive and significant effect on green food purchasing behaviour. More information, experiences, opinions and recommendations on green foods in social media channels can encourage consumers to buy more green food.

This study first evaluates the applicability of the TPB model in explaining green food purchasing behaviour. This study is extended with two new factors included in the original framework of the TPB model, namely, SMU and DMI.

This research paper aims to evaluate the sustainability knowledge and background of students, staff and faculty regarding current university sustainability practices and individual behaviors at Central Michigan University (CMU); to compare sustainability background and knowledge based on academic discipline of enrollment or employment; and to assess sustainability awareness and interest of the campus community to guide future sustainability initiatives and resources at CMU.

An electronic cross-sectional survey was used to collect anonymous responses through Qualtrics, and then results were analyzed through SPSS. Analyses were performed based on the academic structures at CMU.

This research has found that students in STEM fields are more inclined to have pro-sustainability attitudes, knowledge and behaviors, compared to those studying the arts and business. Additionally, results indicate that there is a significant difference in knowledge between the students, and the staff and faculty respondents regarding sustainability knowledge and application, with the staff and faculty consistently demonstrating more pro-sustainability knowledge and behavior.

While research has previously been conducted on sustainability attitudes and behaviors, this research is unique because it ties sustainability knowledge to academic discipline. Additionally, it serves to gauge which sustainability programs and topics members of the campus community are most interested in, and which areas they are most willing to support.

The study aims to determine the role of online retail website experience on brand happiness and willingness to share personal information using the theoretical lens of the Stimulus-Organism-Response (SOR) framework. Further, it explores the role of brand intimacy and brand partner quality in mediating the path between brand happiness and willingness to share personal information.

This study used a cross-sectional survey design to collect data from 439 online retail consumers in India, using an online questionnaire. The data were analysed using Structural Equation Modelling in IBM Amos.

The present study found that online retail website experience is significantly related to brand happiness. The finding also supports that brand happiness was positively and significantly related to ‘consumers' willingness to share personal information. This relationship was fully mediated by brand intimacy. Brand happiness also mediated the relationship between website experience and the willingness to share personal information.

This study contributes to the emerging literature on brand happiness and willingness to share personal information. It establishes a central role of brand happiness as a driver and a mediator of consumers' willingness to share personal information with e-commerce retailers, extending the stimulus-organism-response framework in the context of brand happiness and willingness to share personal information. Further, the study establishes the role of website experience as a marketer (and brand) led driver of brand happiness.

The results have implications for the role of the website in enhancing the consumer experience, which in turn is a driver of brand happiness. Further, managers need to promote brand happiness with the help of website experience to enable consumers’ willingness to share personal information and help organizations customize their marketing campaigns.

This is among the first studies to evaluate brand happiness from the perspective of an online retail website experience and consider consumers’ willingness to share personal information from a branding rather than a technological perspective. Additionally, the study introduces the SOR framework in the context of brand happiness, with website experience acting as a stimulus for consumers, resulting in brand happiness, which is mediated by brand partner quality and brand intimacy (organism), leads to consumers' willingness to share personal information with online retail brands (response).

This study aims to assess the effect of job insecurity, customer incivility and work–life imbalance on Lebanese bank employee workplace well-being (EWW), while investigating the moderating role that positive and negative affect might have.

Quantitative data was collected from 202 respondents and analyzed using structural equation modeling system through IBM SPSS and AMOS.

Results revealed that each of the independent variables has a negative, statistically significant effect on Lebanese bank EWW. The positive affect and the negative one are shown to have a moderating effect that lessens and boosts, respectively, these negative effects.

The study adds to the literature on EWW while highlighting the high-power distance and collectivist society that the research took place in.

Limitations include the sample size that was hoped to be larger, in addition to the self-reporting issue and what it entails in the data collection process.

The study has many practical implications, including the validation of a questionnaire in a developing Arab country, hence providing a reliable tool for researchers. HR specialists should lean toward applicants with positive affect, ensuring that their workplace is occupied by members with enhanced resilience. Furthermore, employers should support their employees’ professional growth, thus, boosting their employability during turmoil and consequently making them less vulnerable in times of economic recession.

The study’s unique context, depicted in the harsh economic and financial crisis, makes the findings on EWW of a high value.

Due to the rapid development of artificial intelligence (AI) technology, increasing the use of AI in healthcare is critical, but few studies have explored the extent to which physicians cooperate with AI in their work to achieve productive and innovative performance, which is a key issue in operations management (OM). We conducted empirical research to answer this question.

We developed a conceptual model based on the ambidextrous perspective. To test our model, we collected data from 200 Chinese hospitals. One senior and one junior physician from each hospital participated in this research so that we could get a more comprehensive view. Based on the sample of 400 participants and the conceptual model, we examined whether different types of AI use have distinct impacts on physicians’ productivity and innovation by conducting hierarchical regression and post hoc tests. We also introduced team psychological safety climate (TPSC) and AI technology uncertainty (AITU) as moderators to investigate this topic in further detail.

We found that augmentation AI use is positively related to overall productivity and innovative job performance, while automation AI use is negatively related to these two outcomes. Furthermore, we focused on the impacts of the ambidextrous use of AI on these two outcomes. The results highlight the positive impacts of complementary use on both outcomes and the negative impact of balance on innovative job performance. TPSC enhances the positive impacts of complementary use on productivity, whereas AITU inhibits the negative impacts of automation and balanced use on innovative job performance.

In the age of AI, organizations face greater trade-offs between performance and technology management. This study contributes to the OM literature from the perspectives of operational performance and technology management in three ways. First, it distinguishes among different AI implementations and their diverse impacts on productivity and innovative performance. Second, it identifies the different conditions under which automation AI use and augmentation are superior. Third, it extends the ambidextrous perspective by becoming an early adopter of this approach to explore the implications of different types of AI use in light of contingency factors.

The purpose of this study is to propose and test an extended theory of planned behavior model to explain the significance of social media influencers’ credibility, social media usage (SMU) and social media marketing while simultaneously examining females’ intentions to purchase cosmetics online.

An online questionnaire was used to collect data from 386 female consumers of cosmetics, and the data were analyzed using partial least squares structural equation modeling (PLS-SEM) with the help of SmartPLS version 4.

First, the results indicated that SMU, social media influencers’ credibility and social media marketing significantly and positively impact the theory of planned behavior components, namely, attitude, subjective norms (SNs) and perceived behavioral control (PBC). Second, results confirmed that attitude, SNs and PBC significantly and positively influenced female consumers’ online purchase intentions (OPIs).

To the best of the authors’ knowledge, this study is one of the first to examine an integrated model that consisted of SMU, social media marketing and social media influencers along with the theory of planned behavior constructs in their proposed research model in the context of cosmetics in India. The study also enriched the body of knowledge about using the PLS-SEM approach to predict OPI for cosmetics.

In the modern digital realm, while artificial intelligence (AI) technologies pave the way for unprecedented opportunities, they also give rise to intricate cybersecurity issues, including threats like deepfakes and unanticipated AI-induced risks. This study aims to address the insufficient exploration of AI cybersecurity awareness in the current literature.

Using in-depth surveys across varied sectors (N = 150), the authors analyzed the correlation between the absence of AI risk content in organizational cybersecurity awareness programs and its impact on employee awareness.

A significant AI-risk knowledge void was observed among users: despite frequent interaction with AI tools, a majority remain unaware of specialized AI threats. A pronounced knowledge difference existed between those that are trained in AI risks and those who are not, more apparent among non-technical personnel and sectors managing sensitive information.

This study paves the way for thorough research, allowing for refinement of awareness initiatives tailored to distinct industries.

It is imperative for organizations to emphasize AI risk training, especially among non-technical staff. Industries handling sensitive data should be at the forefront.

Ensuring employees are aware of AI-related threats can lead to a safer digital environment for both organizations and society at large, given the pervasive nature of AI in everyday life.

Unlike most of the papers about AI risks, the authors do not trust subjective data from second hand papers, but use objective authentic data from the authors’ own up-to-date anonymous survey.

The purpose of this paper is to investigate the moderating effect of homophily between trust in social media influencers (SMIs) and credibility of the post in influencer marketing by incorporating the similarity attraction theory (SAT) and analysing the effect of trust in SMIs on online purchase intention and credibility of the post. This study also explored the mediating role of influencers’ credibility of the post between trust in SMIs and online purchase intention.

The data were collected from 417 respondents in Jaipur, India, using an online questionnaire via Google Forms. A convenience sampling technique was employed to collect the data. Partial least squares structural equation modelling (PLS-SEM) was used to test the proposed hypotheses with the help of SmartPLS version 4.

The results exhibit a positive and significant influence of trust in SMIs on credibility of the post and online purchase intention. Also, this study found a positive and significant relationship between credibility of the post and online purchase intention. Additionally, credibility of the post had a positive and significant mediation role in the relationship between trust in SMIs and online purchase intention. In addition, homophily positively moderated the relationship between trust in SMIs and credibility of the post.

The findings of this study can be used by marketing professionals working in the e-commerce industry to ensure their continued in success using the right influencers for their specific target audiences and help them create and implement more effective promotional strategies, increasing brand awareness, announcing sales, using them for creative content and so on.

Until now, there has been no study in the Indian context that has tested the moderation effect of homophily between the trust in SMIs and credibility of the post by incorporating the SAT, according to the researchers’ knowledge. Furthermore, this novel piece of research explored the relationship between trust in SMIs and online purchase intention with credibility of the post as a mediator.