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Chocolate production and cocoa supply chains are rife with social and environmental challenges. Chocolate companies commonly make claims that their products are “sustainable”, giving little guidance on what this means. The aim of this paper is to conduct a scoping review to synthesise the accounting literature related to the chocolate industry and sustainability and develop a research agenda for accounting scholarship.

The scoping review followed Arksey and O’Malley’s (2005) five-stage framework for a scoping review. Nineteen accounting journals were searched for literature on “chocolate OR cocoa AND sustainability” from 2000 to 2023. A total of 171 papers were identified through the search, of which 18 were deemed relevant and included for thematic analysis. The themes are analysed using a conceptual framework on accountability.

Analysis of the relevant literature revealed three distinct perspectives on sustainability in the chocolate industry. These include critique on the problems related to top-down accountability approaches in the chocolate industry; that accountability mechanisms have fallen short in managing sustainability challenges; and that sustainability interventions are driven by profit motives. The themes further reveal a lack of accountability in the industry for marginalised voices.

The scoping review methodology used in this study offers insights into the diverse perspectives on sustainability in the chocolate industry. This research adds valuable knowledge to the field by uncovering nuanced issues around accountability and sustainability and highlighting the need for future research for accountability for sustainable chocolate production.

This paper explores the significance of work-based learning in the context of leadership development, organizational growth and the promising economic success in Tennessee organizations. It aims to investigate the practical implications of work-based learning, focusing on its role in enhancing leadership capabilities, fostering innovation and contributing to a prosperous economic future.

The research employs a systematic literature review to examine existing studies on work-based learning, leadership development, organizational growth and economic success in Tennessee. It also involves data collection from various sources, including government agencies, colleges and organizations in the state. The collected data are rigorously verified and cross-referenced to ensure reliability and relevance.

The findings emphasize the transformative potential of work-based learning initiatives in Tennessee. They reveal that work-based learning programs are vital in developing influential leaders, fostering a culture of learning and innovation and contributing to economic competitiveness. The research also highlights the interconnectedness of leadership development, organizational growth and economic success, emphasizing the critical role of work-based learning in driving positive outcomes in all these dimensions.

This research contributes to the existing body of knowledge by emphasizing the practical applicability of work-based learning findings. It provides insights into the unique context of Tennessee organizations and their motivations, challenges and opportunities related to work-based learning. The research also outlines recommendations and future research directions to bridge the gap between theory and practice, enhancing the impact of work-based learning initiatives in Tennessee and beyond. The insights gained can assist other states and industries in developing effective work-based learning programs tailored to their specific economic needs and industry demands, fostering broader economic prosperity.

This study describes a short-term project designed for students to develop important skills needed for artificial intelligence (AI) literacy and to understand how the concepts of AI literacy may be viewed in different countries.

This mixed-methods study sets out to investigate students’ perceptions on the use of AI-generated communication in the workplace, particularly the use of ChatGPT for business communication. We discuss student responses to questions regarding AI-generated business communication according to the diamond model of AI literacy.

This study’s findings reflect students’ awareness of the use of AI at their workplace, their perceptions of the benefits and challenges of AI-generated business communication, as well as their perceived need for institutionalizing policies at their respective companies. The study reports on potential differences in cultural attitudes regarding generative AI.

This study involved a project with a limited sample. It involved students in the United States of America, Germany and India and was replicated. Despite the sample size, we feel it has relevance for underlining opportunities for AI literacy skills in higher education (HE) institutions, especially in terms of heightening awareness of cultural appropriateness, sensitivity towards data privacy needs and developing students' intercultural communication skills.

The following study addresses the need for institutions of HE to develop students’ AI literacy, including how concepts of AI literacy may be viewed differently and how AI-generated business communication must be adapted to suit diverse environments. The study encourages instructors to incorporate AI tools in their curricula by illustrating one best use-case for developing students’ abilities to utilize this technology for professional business communication.

Employing the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, this study examines the potential differences between two groups of hotel guests – business and leisure travelers – in terms of factors influencing their intention to purchase hotel products on Douyin (TikTok) in China.

Data gathered from 700 Chinese hotel guests was analyzed using partial least squares-structural equation modeling (PLS-SEM) and multigroup analysis (MGA).

The MGA results reveal that three newly added variables – personalization, perceived interactivity and perceived creativity – significantly influence the purchase intention of leisure travelers but not business travelers. Regarding the conventional UTAUT2 variables, leisure travelers are more influenced by hedonic motivation and price value in their purchasing decisions. In contrast, performance expectancy and effort expectancy have a greater impact on the decision-making process of business travelers than their leisure counterparts.

Theoretically, this paper is among the first to explore traveler types as moderators in the purchase of hotel products on Douyin. Practically, the findings offer valuable guidance for hotel marketers aiming to leverage Douyin to promote hotel products to these two different traveler segments.

Instead of using “one-size-fits-all” strategies, hotel managers should design marketing strategies that address the diverse needs of business and leisure travelers on Douyin. By implementing this strategy, they can effectively attract target customers and, in turn, increase hotel revenue.

This study expands the UTAUT2 framework and contributes to the scarce knowledge about the differences between business and leisure travelers regarding the relative importance of factors that influence their purchase intention for hotel products on Douyin among business and leisure travelers.

The use of digital technology is crucial for building resilience and shaping competitive advantages in project-based organizations (PBOs). The purpose of this study is to explore the impact of digital elements on organizational resilience and resilience enhancement paths in PBOs represented by the construction industry in the context of digitization.

This study uses multivalue-set qualitative comparative analysis (mvQCA). First, we collect digitization keywords from the annual reports of PBOs in the construction industry and classify them as process digitization, digital technology application and production intelligence while also considering word frequency statistics as antecedent conditions. Second, through a literature review and the use of the data collected, we define organizational resilience as the ability of organizations to defend, resist, recover and develop. Then, we use the mvQCA approach to examine how digital antecedent variables collectively advance PBO resilience.

By collecting data on 79 listed Chinese construction companies and utilizing mvQCA, we identify five combinations of conditions that produce high levels of organizational resilience, and the solution coverage is 1. These methods are (1) digital technology application-oriented, (2) process digitalization-oriented, (3) digitized multifactor coupling, (4) process digitization and digital technology application-driven and (5) process digitalization and production intelligence-driven.

These findings have important theoretical and practical implications for revealing the digital-driven path to high levels of PBO resilience. In theory, this study enriches the research on organizational resilience and expands the application scope of organizational resilience theory and the QCA method. Furthermore, this study provides new ways and ideas for PBOs to effectively integrate and utilize internal and external digital resources to increase their levels of organizational resilience.

Competition is one of the least used social marketing principles. Yet, an assessment of direct competition is one of the key factors defining social marketing from other behavioural change approaches. This paper aims to synthesise literature from evidence reviews assessing the extent that competitive analysis has been undertaken. This paper contributes a new competitive analysis method that can be incorporated within the seven-step co-design process delivering an alternative tool that social marketers can consider. Competition assessment enables social marketers to identify cooperators, share resources and ultimately enhance social marketing programme success.

A synthesis on competition assessments reported in 30 evidence review studies is provided. This paper offers a new competition analysis method that can be applied to undertake competitive assessments demonstrating likes, dislikes and other ideas, which can be gathered during the sensitisation phase of co-design.

Out of the 1,795 papers suitable for title/abstract screening, 30 evidence reviews assessing extent of competition use or extracting detail on competition from selected studies in the review were included in this umbrella review. Heterogeneity was evident, with reviews concluding between 0% and 100% competition use. Social marketers generally lack resources and can benefit from an easy way of defining and examining competition and this can be done by considering only direct competition.

This rapid review synthesises the author’s views and is limited to studies identified within the 30 evidence reviews considered. Future research directions are outlined.

Competitive assessments are akin to standing on the shoulders of giants. Competitive assessments allow you to identify what individuals like and do not likev and potential cooperators that can be partnered with to reduce noise, which can better support people to make choices that achieve intended programme outcomes and deliver benefits to individuals.

Increased utilisation of the competition criteria will help to avoid costly failures ensuring that social marketers have improved odds of programme success. Through identifying programmes that are currently available, which people like, social marketers can establish partnerships to share resources driving more effort to delivering outcomes.

This paper offers a new competition assessment method for resource constrained social marketers that can be incorporated into the Trischler et al. (2019) seven-step co-design process. Increased application of competition will enhance social marketing effectiveness.

This paper aims to explore the impact of the data observation period on the computation of altmetric measures like velocity index (VI) and half-life. Furthermore, it also attempts to determine whether article-level computations are better than computations on the whole of the data for computing such measures.

The complete publication records for the year 2016 indexed in Web of Science and their altmetric data (original tweets) obtained from PlumX are obtained and analysed. The creation date of articles is taken from Crossref. Two time-dependent variables, namely, half-life and VI are computed. The altmetric measures are computed for all articles at different observation points, and by using whole group as well as article-level averaging.

The results show that use of longer observation period significantly changes the values of different altmetric measures computed. Furthermore, use of article-level delineation is advocated for computing different measures for a more accurate representation of the true values for the article distribution.

The analytical results show that using different observation periods change the measured values of the time-related altmetric measures. It is suggested that longer observation period should be used for appropriate measurement of altmetric measures. Furthermore, the use of article-level delineation for computing the measures is advocated as a more accurate method to capture the true values of such measures.

The research work suggests that altmetric mentions accrue for a longer period than the commonly believed short life span and therefore the altmetric measurements should not be limited to observation of early accrued data only.

The present study indicates that use of altmetric measures for research evaluation or other purposes should be based on data for a longer observation period and article-level delineation may be preferred. It contradicts the common belief that tweet accumulation about scholarly articles decay quickly.

Several studies have shown that altmetric data correlate well with citations and hence early altmetric counts can be used to predict future citations. Inspired by these findings, majority of such monitoring and measuring exercises have focused mainly on capturing immediate altmetric event data for articles just after the publication of the paper. This paper demonstrates the impact of the observation period and article-level aggregation on such computations and suggests to use a longer observation period and article-level delineation. To the best of the authors’ knowledge, this is the first such study of its kind and presents novel findings.