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This study aims to delve into the underlying factors that play a pivotal role in shaping effective digital marketing communication (DMC) to promote sustainability. Further, it explores the mediating effect of online customer experience (OCE) on the dynamic relationship between DMC and sustainable purchase intention (SPI) and the moderating impact of social media marketing activities (SMMAs) on the relationship between DMC and OCE.

Based on single cross-sectional survey, 300 responses from green apparel users are analyzed by using partial least squares-structural equation modeling to corroborate the relationships among DMC, OCE, SMMAs and SPI.

Perceived usefulness, ease of use, web attractiveness, hedonic motivation and subjective norms significantly impact DMC, which in turn positively influences OCE and SPI. Further, OCE significantly mediates the relationship between DMC and SPI, highlighting the crucial role of OCE. The moderation analysis shows that interactivity negatively moderates the DMC-OCE relationship, suggesting that excessive interactivity may diminish the OCE, while personalization and trendiness do not have significant moderating effects.

The findings provide valuable insights for marketers to align their DMC strategies with sustainable business initiatives to create a seamless online experience, thereby fostering SPI in the contemporary digital era.

While previous studies have examined aspects of these relationships separately, this study integrates them into a cohesive framework to provide a more holistic understanding of how digital marketing strategies can promote sustainability.

The purpose of the study is to examine the factors that influence people's intention to adopt electric vehicles (EVs). The study used an expanded theory of planned behaviour (TPB) along with the addition of perceived trust and consideration of future consequences (CFC).

The study is based on primary data collected from 282 respondents in Punjab through a questionnaire. The collected data were analysed using SPSS 26 and AMOS 24 to perform confirmatory factor analysis and structural equation modelling.

The empirical analysis indicates that attitude, subjective norms and perceived trust have a significant influence on the adoption intention (AI) of EVs.

The implications provide policymakers and marketers with better insights into marketing EVs in the trajectory of sustainable mobility. Marketers should create focussed marketing materials that highlight the environmental ease of use, lower running costs and sophisticated technology of electric automobiles. The limitations of the study provide valuable insights for future researchers.

This is the first study that uses CFC with the TPB model in the context of AI of EVs specifically for the Punjab region.

This chapter focuses on the integration of virtual reality (VR) into human resource management (HRM), with a special emphasis on theoretical underpinnings that support its adoption and utilisation. The speed at which technology is improving has placed VR as potentially game-changing for the field of HRM. This chapter reviews a number of theoretical models, including the Technology Acceptance Model, Unified Theory of Acceptance and Use of Technology, Diffusion of Innovations Theory and Social Cognitive Theory, in an attempt to make the framework as exhaustive as possible in the quest to unravel the ingredients that influence the acceptance of VR in HRM. This chapter discusses the practical implications of VR on the enhancement of organisational efficiency and employee well-being, based on a literature review of empirical studies that shed light on the challenges for VR applications due to technical limitations, ethical concerns and people's resistance to change. It concludes by indicating the literature gaps and proposing some future lines of research for the use of VR in HRM.

In construction projects, engineering variations are very common and create breeding grounds for opportunistic claims. This study investigates the complementary effect between an inspection mechanism and a reputation system in deterring opportunistic claims, considering an employer with limited inspection accuracy and a contractor, which can be either reputation-concerned or opportunistic.

This paper applies a signaling game to investigate the complementary effect between the employer's inspection and a reputation system in deterring the contractor's possible opportunistic claim, considering the information-flow influence of claiming prices.

This study finds that in the exogenous-inspection-accuracy case, the employer does not always inspect the claim. A more stringent reputation system complements a less accurate inspection only when the inspection cost is lower than a threshold, but may decline the employer's surplus or social welfare. In the optimal-inspection-accuracy case, the employer always inspects the claim. However, only a sufficiently stringent reputation system can guarantee the effectiveness of an optimal inspection in curbing opportunistic claims. A more stringent reputation system has a value-stepping effect on the employer's surplus but may unexpectedly impair social welfare, whereas a higher inspection cost efficiency always reduces social welfare.

This article contributes to the project management literature by combing the signaling game theory with the reputation theory and thus embeds the problem of inspection mechanism design into a broader socio-economic framework.

This study investigated leaders’ decision-making during crises. Using grounded theory research, we explored whether leaders’ use of either individualistic or collectivistic decision-making styles is based on the context of a crisis. In addition, the authors looked into the components of building leaders’ efficacy during a crisis event and gauged their attitudinal and behavioral reactions to the crisis.

The authors conducted interviews with 30 C-suite executives during the first wave of the COVID-19 pandemic to determine their responses to crises. The authors then used open, axial, and selective coding to examine their data, which was then extracted for representative themes and overarching dimensions. In total, The authors received 12 major themes largely summarizing into 6 overarching dimensions – context of decision-making, leaders’ efficacy, individualistic approach to decision-making, collectivistic approach to decision-making, process of decision-making, and outcomes.

The research presents a decision-making framework clearly bifurcating situations with the need for individualistic and collectivistic decision-making. While, a high level of urgency and scarce resources encouraged leaders to adopt an individualistic approach in which most of the decisions were intuition-based and only high-level stakeholders were involved, the less time urgent and uncertain situation allowed leaders to put significant effort into building their own knowledge systems and involving others. In addition, leaders’ efficacy is understood in terms of their attitudes, readiness and reactions, which further elaborated upon their knowledge systems to allow them to excel in decision-making irrespective of the approaches they chose.

The research has implications for leaders in the decision-making roles to be effective during both individualistic and collectivistic decision-making.

Despite firms’ growing investments, process improvement (PI) programs often fail to deliver the expected benefits. In this paper, we argue that the widespread adoption in PI research of a paradigm founded in positivism plays a primary role in deriving these conclusions and limits the development of PI theory and practice.

We examine the main characteristics of the dominant paradigm in PI research and then propose an alternative perspective drawing on research in management innovation and complexity. Findings from two empirical case studies in a pharmaceutical and an automotive firm are reported to support our theoretical argument.

The proposed perspective highlights the interaction between various PI approaches – such as lean, Six Sigma and total quality management (TQM) – and the context-dependence and experiential aspects of PI. We argue that this perspective can better account for where, by whom and how PI approaches are shaped and used and, ultimately, can more effectively advance both theory and practice.

This study suggests that PI approaches should be considered as adaptable rather than static, in combination rather than as single entities and as continuously interpreted and translated by organizational actors rather than homogeneously diffused across companies and business units. In this paper, we discuss the substantial conceptual, methodological and practical implications of adopting this perspective.

Flood preparedness and response from the perspective of community engagement mechanisms have been studied in scholarly articles. However, the differences in flood mitigation may expose social and behavioural challenges to learn from. This study aimed to demonstrate how text mining can be applied in prioritising existing contexts in community-based and government flood mitigation and management strategies.

This investigation mined the semantics researchers ascribed to flood disasters and community responses from 2001 to 2022 peer-reviewed publications. Text mining was used to derive frequently used terms from over 15 publications in the Scopus database and Google Scholar search engine after an initial output of 268 peer-reviewed publications. The text-mining process applied the topic modelling analyses on the 15 publications using the R studio application.

Topic modelling applied through text mining clustered four (4) themes. The themes that emerged from the topic modelling process were building adaptation to flooding, climate change and resilient communities, urban infrastructure and community preparedness and research output for flood risk and community response. The themes were supported with geographical flood risk and community mitigation contexts from the USA, India and Nigeria to provide a broader perspective.

This study exposed the deficiency of “communication, teamwork, responsibility and lessons” as focal themes of flood disaster management and response research. The divergence in flood mitigation in developing nations as compared with developed nations can be bridged through improved government policies, technologies and community engagement.

Building a robust cold chain logistics system boosts the company’s profits in various ways. Any cold chain logistics company needs well-organised and efficient management of cold chain logistics to produce high-quality products, ensure that the product reaches the customer without any changes to the quality, and do so promptly. This paper aims to identify factors influencing cold chain logistics performance design. These factors are further helpful in analysing the behaviour intentions of stakeholders on increasing the cold chain logistic performance.

The authors conducted a thorough literature review to identify the variables that affect the performance of the cold chain logistics design. The factors were identified using exploratory factor analysis and empirically analysed using confirmatory factor analysis. The study also used structural equation modelling (SEM) to examine cold chain logistics performance determinants. Data was collected from 380 respondents working in the cold chain.

This study selected the factors influencing CCL performance, including five main factors and 22 sub-factors. Distribution, warehouse inventory storage, quality, demand, and technology affect the CCL’s performance. The results confirmed the theoretical model and proved that the factors significantly positively impact CCL performance.

Future studies should focus on actual case studies to confirm the usefulness of the parameters found, examine how they affect performance growth, provide important insights into how to improve overall business performance and assist in identifying crucial research hotspots.

The study provides insight into issues regarding performance development in cold chain logistics for various stakeholders associated with the cold chain logistics industry, including practical managers, academics, and consultants. It also argues in favour of giving problems with CCL performance a higher priority. Policymakers interested in the service sector, like the Indian Department of Commerce and MSMEs, make up a modest additional audience for this work.

Indian meat industry can be organised by implementing this methodology. This work benefits the government to get more transparent transaction and data digitalisation, which comes into account of GST.

There is a lack of significant quantitative literature suggesting modification strategies for factors affecting processed meat and chicken products in storage and transportation levels in India. Thus, this work tried to fill this gap and add the food chain logistics literature that helps practitioners and scholars enhance the food supply chain in developing countries.The framework developed for this study is where its originality lies. A detailed examination of cold chain logistics is included in the paper.

Drawing on the technology affordance and affinity theories, this study proposes a framework explaining the antecedents and consequences of customers’ smart experiences (CSEs) in the artificial intelligence (AI) chatbot context.

The quantitative approach employing an online survey was adopted to obtain data from chatbot users (N = 761) and analyzed using structural equation modeling.

Results from a survey study show that chatbot affordances, including interactivity (two-way communication, active control and synchronicity), selectivity (customization and localization), information (argument quality and source credibility), association (connectivity and sense of safety) and navigation positively affect CSEs (hedonic and cognitive), leading to customer chatbot stickiness through affinity.

Our study provides evidence that supports and extends the affordances and affinity lens by highlighting the roles of specific chatbot affordances that contribute to a positive-smart experience and subsequently enhances customer chatbot stickiness through affinity.