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The purpose of this research is to identify and analyse the perceived risk factors affecting the safety of electric two-wheeler (E2W) riders in urban areas. Given the exponential growth of the global E2W market and the notable challenges offered by E2W vehicles as compared to electric cars, the study aims to propose a managerial framework, to increase the penetration of E2W in the emerging market, as a reliable, and sustainable mobility alternative.

The perceived risk factors of riding E2Ws are relatively scanty, especially in the context of emerging economies. A mixed-method research design is adopted to achieve the research objectives. Four expert groups are interviewed to identify crucial safety risk E2W factors. The grey-Delphi technique is used to confirm the applicability of the extracted risk factors in the Indian context. Next, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is employed to reveal the causal-prominence relationship among the perceived risk factors. The dominance and prominence scores are used to perform Cause and Effect analysis and estimate the triggering risk factors.

The finding of the study suggests that reckless adventurism, adverse road conditions, individual characteristics and distraction caused by using mobile phones, as the topmost triggering risk factors that impact the safety of E2Ws drivers. Similarly, reliability on battery performance low velocity and heavy traffic conditions are found to be some of the critical safety factors.

E2Ws are anticipated to represent the future of sustainable mobility in emerging nations. While they provide convenient and quick transportation for daily urban commutes, certain risk factors are contributing to increased accident rates. This research analyses these risk factors to offer a comprehensive view of driver and rider safety. Unlike conventional measures, it considers subjective quality and reliability parameters, such as battery performance and reckless adventurism. Identifying the most significant causal risk factors helps policymakers focus on the most prominent issues, thereby enhancing the adoption of E2Ws in emerging markets.

We have proposed an integrated framework that uses grey theory with Delphi and DEMATEL to analyse the safety risk factors of driving E2W vehicles considering the uncertainty. In addition, the amalgamation of Delphi and DEMATEL helps not only to identify the pertinent safety risk factors, but also bifurcate them into cause-and-effect groups considering the mutual relationship between them. The framework will enable practitioners and policymakers to design preventive strategies to minimize risk and boost the penetration of E2Ws in an emerging country, like India.

Witness-led techniques, informed by theory, have been recognized as best practice for eliciting information from cooperative eyewitnesses. This study aims to test a self-generated cue (SGC) mnemonic grounded in memory theory and explore the impact of three SGC mnemonics on subsequent recall performance.

Participants (N = 170) witnessed a live staged event and reported their recall using an SGC mnemonic (keywords only, event line or concept map) or control technique (other-generated cues or free recall only). These mock witness accounts were compared in terms of correct and incorrect details reported.

Fewer correct details were reported in the other-generated cue condition compared to the SGC event line (p = 0.018) and SGC concept map (p = 0.010). There were no significant differences between free recall alone and any other condition. The number of inaccurate details reported did not differ between conditions (p = 0.153). The findings suggest that high-quality free recall instructions can benefit recall performance above generic cues (e.g. other-generated cues) but using SGCs to support a structured recall (e.g. concept map or event line) may offer an additional recall benefit.

The findings support previous research that SGCs benefit recall beyond other-generated cues. However, by comparing different cue generation techniques grounded in the literature, we extend such findings to show that SGC generation techniques are not equally effective and that combining SGCs with structured recall is likely to carry the greatest benefit to recall.

The impact of mankind on the environment and the usage of natural resources might be influenced by spirituality, through the consciousness of creating an improved moral sense regarding the consequences of human activities and the necessity to alter these to achieve sustainable development. However, the spiritual element in the form of ecospirituality (ES) has not been sufficiently considered in pro-environmental studies as it relates to the influence of green training (GT) on voluntary workplace green behaviour (VWGB) in the construction sector. This study aims to determine the effect of GT on VWGB and the mediating effect of ES on the relationship between GT and VWGB on construction projects.

This study’s data were gathered through a questionnaire survey of construction site managers and project managers by adopting the probability sampling method. 249 appropriately completed questionnaires were returned. The data obtained were analysed by means of the partial least squares structural equation modelling technique (PLS-SEM).

The outcomes of the study show that GT has a significant positive impact on VWGB, while ES has a significant mediating effect on the relationship between GT and VWGB, both supporting the study’s hypotheses.

These findings point to the fact that the hitherto conflicting results reported in earlier studies on the GT–VWGB relationship can be attributed to the lack of consideration given to ES. Hence, special attention should be given to ES.

This research presents actions to enhance the transformation of GT into VWGB by giving due consideration to ES, which was not taken into account in previous studies.

Obesity imposes myriad negative consequences upon society, the economy and personal well-being. This study aims to investigate the effectiveness of using political correctness (PC) in social marketing messages to persuade consumers to change their unhealthy behavior. It also explores various underlying mechanisms that drive this effect. Specifically, this research studies that messaging approach – politically correct vs politically incorrect and gain vs loss message framing – generates higher consumer intentions to change their behavior.

Four experiments were conducted with nationally representative samples to examine the effect of PC and gain vs loss message framing on consumers’ behavior changing intentions.

Politically correct prosocial marketing messages displayed higher persuasiveness than politically incorrect messages. Each relationship was mediated by the perceived manipulative capacity of the message and consumers’ attitudes toward the message. Message framing performed as a boundary condition for these effects.

This paper sought to contribute to the literature that investigates the effectiveness of social marketing efforts. Three specific contributions related to the effects of message frames on politically correct and incorrect social marketing messages were developed.

The strategies presented in this paper benefit firms wishing to create a more prosocial approach to their business. A firm can present a prosocial message to their target market in a frame focusing on what will be gained instead of lost. Likewise, firms should welcome this type of messaging that embraces politically correct terminology instead of shying away from it.

This paper generates actionable insights for marketers and policymakers regarding how best to communicate with targeted segments about culturally- and personally sensitive topics related to obesity and weight loss. This paper also contributes to the literature that explores the effectiveness of social marketing initiatives. The findings suggest policymakers and social marketers should be cautious and, regardless of today’s sociopolitical environment, avoid falling into the temptation of developing politically incorrect and loss-framed messages.

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

The purpose of this study is to examine the buyers’ preferences influencing the purchase of privately developed affordable housing in Kolkata and to determine whether unsold houses result from misalignment with these preferences.

The literature review and user-opinion survey identified 119 independent variables that indicate buyers’ preferences. A questionnaire survey of 383 households in affordable housing units from 32 housing complexes in Kolkata recorded buyers’ preferences and satisfaction against the independent variables grouped under five levels of characteristics. The product weights of variables derived from the rank sum method and percentage satisfaction give the Utility Score. Multivariate regression and univariate linear regressions were conducted to determine the significance of each Level of characteristics and each variable, identifying the significant variables that would affect the sale of affordable houses.

The multivariate regression analysis has indicated that 68.56% of the variation in the percentage of unsold houses was explained by the five utility scores, which affirms that misalignment with buyers’ preferences significantly affects the sale of privately developed affordable houses. Furthermore, building and neighbourhood-level utility show the highest significance as predictors, while city-level and miscellaneous utility have moderate significance, but housing complex-level utility lacks statistical significance.

This study addresses a research gap in privately developed affordable housing in Kolkata, enhancing understanding of buyer preferences in this segment.

Recognition of the complexity of job embeddedness in the work environment has grown, highlighting the need for a deeper understanding of the factors that contribute to this phenomenon. This study analyzed how and when job crafting and leisure crafting are linked to job embeddedness by investigating employee resilience as a mediator and employee adaptivity as a moderator.

Data were gathered from 568 Taiwanese hotel employees. The PROCESS macro was used to verify all hypotheses.

Both job crafting and leisure crafting increased job embeddedness. Employee resilience mediated the impacts of job and leisure crafting on job embeddedness. The positive relationship between employee resilience and job embeddedness was stronger when employee adaptivity was high. Employee adaptivity moderated the indirect impacts of job and leisure crafting on job embeddedness through employee resilience.

Hotel managers should foster a workplace culture that encourages employees to engage in job crafting. Additionally, managers can offer employee assistance programs to proactively encourage workers to participate in leisure crafting. Providing training and wellness programs to strengthen employee resilience, along with allocating resources and designing learning programs to enhance employee adaptability, can further promote job embeddedness.

This research contributes to the literature through the construction of a moderated mediation model that explored how and when job and leisure crafting affect job embeddedness.

This study aims to uncover the ongoing discourse on generative artificial intelligence (AI), literacy and governance while providing nuanced perspectives on stakeholder involvement and recommendations for the effective regulation and utilization of generative AI technologies.

This study chooses generative AI-related online news coverage on BBC News as the case study. Oriented by a case study methodology, this study conducts a qualitative content analysis on 78 news articles related to generative AI.

By analyzing 78 news articles, generative AI is found to be portrayed in the news in the following ways: Generative AI is primarily used in generating texts, images, audio and videos. Generative AI can have both positive and negative impacts on people’s everyday lives. People’s generative AI literacy includes understanding, using and evaluating generative AI and combating generative AI harms. Various stakeholders, encompassing government authorities, industry, organizations/institutions, academia and affected individuals/users, engage in the practice of AI governance concerning generative AI.

Based on the findings, this study constructs a framework of competencies and considerations constituting generative AI literacy. Furthermore, this study underscores the role played by government authorities as coordinators who conduct co-governance with other stakeholders regarding generative AI literacy and who possess the legislative authority to offer robust legal safeguards to protect against harm.

This study aims to perform the bibliometric analysis of the customer engagement (CE) literature, highlights the major research themes and classifies the subdomains. The study also identifies antecedents and consequences, as well as dimension evolution, and suggests future research directions.

This study used a comprehensive bibliometric approach using Scopus data from 2002 to January 2024. Advanced analytical techniques, including bibliometric and cocitation analysis using R and bibexcel, were used. In addition, machine learning (ML)-based Latent Dirichlet Allocation (LDA) was used to extract latent themes.

This study reveals the domain’s past trend and present research scenario. The thematic analysis of CE is classified into three phases. Document cocitation analysis provided four broad clusters: conceptualization and operationalization, value creation through engagement, building relationships with brands and engagement-social media interface. The antecedents and consequences are categorized and presented along with the evolution of the multidimensional nature of CE.

This study adds to the literature in two key ways. First, the entire scholarly production has been compiled into one frame. Second, multiple methods were used to unravel citation, cocitation and textual data. Furthermore, ML-based LDA was used to extract latent themes from clusters and future research directions were proposed.