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The purpose of this paper is to help better understand the translation process of the management control system (MCS) of privatised solid waste management (SWM) towards creating a stable network.

Drawing on the actor network theory (ANT), the case of a privatised SWM was studied. Data were collected from all entities involved in the privatisation process of SWM, which include Department A, Corporation X and the private sector concessionaire. Six documents were reviewed, 20 interviews were conducted and two observations were carried out.

The findings reveal that the control mechanism of SWM is complex, involving the interaction between human and non-human actors. Non-human actors include the key performance indicators (KPIs) and the concessionaire agreement (CA), which are the main control mechanisms towards creating a stable SWM network. Essentially, stability is achieved when the KPIs and CA can influence the activities of both intra- and inter-organisational relationships.

This paper provides a better understanding of the translation process of the MCS that adds to the stability of the network of a privatised SWM from the lens of the ANT.

This paper aims to map the research on management accounting (MA), clarifying its current role and identifying gaps and opportunities for future research.

In this paper, 784 papers were reviewed for the 1958–2019 period, published in 220 scientific journals indexed on Clarivate Analytics’ Web of Science (Science Citation Index Expanded [SCI-EXPANDED] and Social Sciences Citation Index [SSCI]). In the process, content analysis, regression analysis and bibliometric analysis were used.

The most relevant journals, authors and topics in MA, along with trends and patterns in the literature, were identified. Seven clusters that represent the overall thematic research structure of the MA field were also identified. This study shows that MA is becoming a multidimensional management decision-support instrument covering all organizational dimensions. As such, the research on MA is following the recent concerns with the sustainable development and digitalization of business processes.

Based on the findings of this research study, theoretical and practical implications for MA researchers were provided. These findings could also be useful to industry practitioners to improve their knowledge of emerging trends in MA practices, strategies and concepts.

Based on bibliometric and content analysis, a framework that shows an organizational, market and social context for the evolution of MA over the past 60 years was provided. It highlights the dynamics of MA alignment with organizational and external environment changes. Future research opportunities and implications for researchers and practitioners were also identified.

The purpose of this study is to analyze state-of-the-art knowledge of artificial intelligence (AI) research in hospitality.

This study adopts the theory-context-methods framework to systematically review 100 AI-related articles recently published (i.e. from 2021 to April 2023) in three top-tier hospitality journals, namely, the International Journal of Contemporary Hospitality Management, International Journal of Hospitality Management and Journal of Hospitality Marketing and Management.

Findings suggest that studies of AI applications in hospitality are mostly theory-driven, whereas most AI methods research adopts a data-driven approach. State-of-the-art AI applications research exhibits the most interest in service robots. In AI methods research, little attention was paid to the amid-service/experience.

This study reveals inadequacies in theory, context and methods in contemporary AI research. More research from hospitality suppliers’ perspectives and research on generative AI applications are advocated in response to the unveiled research gaps and recent AI developments.

This study classifies the most recent AI research in hospitality into two main streams – AI applications research and AI methods research – and discusses the gaps in each research stream and latest AI developments. The paper then suggests future research directions to guide researchers in advancing AI research in hospitality.

This study examined perceived brand attractiveness of and identification with fashion luxury brands given different levels of sexuality in advertisements. Sex in advertisements has become increasingly more common to generate attention and interest in fashion luxury products, with limited research on its influence on the consumer. However, the use of sexuality in luxury advertisements may counter the ethical expectations of brands by the current consumer in the United States.

A sample of 1,266 males and females completed a survey on brand attractiveness and identification after examining an advertisement of a luxury fashion product. Participants were assigned an advertisement that featured a same-gendered model at one of four levels of sexuality (fully clothed to nude). IBM SPSS Statistics was used to analyze the data which included descriptive statistics and a two-way multivariate analysis of variance followed by an analysis of variance.

The results indicated that less sexuality in luxury advertisements was better in generating attractiveness to and identification with the brand. The advertisements with models fully clothed were rated highest on brand attractiveness and identification. These relationships were statistically significant among groups of men and women.

These findings are important to scholars and marketers of luxury brands as sexuality in luxury brands continues to increase and becomes more provocative, as well as socially conscious.

The purpose of this study is to systematically examine and compare the growth of halal tourism and hospitality in OIC and non-OIC countries based on published literature.

A critical systematic review of 154 academic papers published in the last decade involving halal tourism in OIC and non-OIC countries constituted the sample for this study. The study uses an integrated antecedents, decisions and outcomes and theories, contexts and methods framework, and a coding protocol based on the preferred reporting items for systematic reviews and meta-analyses.

Halal tourism is not developed in non-OIC countries where Islam does not predominate, which represents an opportunity for many countries to incorporate new trends in their tourism offerings. This research increases awareness of non-OIC destinations to welcome a growing halal tourism market, enabling them to foster innovation to meet new demands for Muslim travelers.

This study is different as we compare the pertinent needs that are based on religion in various geographical locations while focusing on tourism and hospitality research in Islamic and non-Islamic nations.

The purpose of this study is to describe latent classes explaining the innovation logic in the Finnish construction companies. Innovativeness is a driver of competitive performance and vital to the long-term success of any organisation and company.

Using finite mixture structural equation modelling (FMSEM), the authors have classified innovation logic into latent classes. The method analyses and recognises classes for companies that have similar logic in innovation activities based on the collected data.

Through FMSEM analysis, the authors have identified three latent classes that explain the innovation logic in the Finnish construction companies – LC1: the internal innovators; LC2: the non-innovation-oriented introverts; and LC3: the innovation-oriented extroverts. These three latent classes clearly capture the perceptions within the industry as well as the different characteristics and variables.

The presented latent classes explain innovation logic but is limited to analysing Finnish companies. Also, the research is quantitative by nature and does not increase the understanding in the same manner as qualitative research might capture on more specific aspects.

This paper presents starting points for construction industry companies to intensify innovation activities. It may also indicate more fundamental changes for the structure of construction industry organisations, especially by enabling innovation friendly culture.

This study describes innovation logic in Finnish construction companies through three models (LC1–LC3) by using quantitative data analysed with the FMSEM method. The fundamental innovation challenges in the Finnish construction companies are clarified via the identified latent classes.