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This study examines the role of technology as a driver of sustainable tourism perceptions among Generation Z.

The work considers the perspective of locals in Pakistan and uses a multi-method, multiphase embedded research design approach.

The research findings demonstrated that technology has a positive correlation with the environmental, socio-cultural and economic dimensions of sustainable tourism perception among Generation Z. Therefore, technology could be considered a dimension of sustainable tourism perception for locals, but perceptions differ significantly depending on the size of the city of the participant. The results of the experimental design phase that utilized picture stimuli demonstrated a linear relationship between technology and sustainability and enhanced their definition and implementation for developing countries.

This research diverges from most past research on these topics by focusing on Generation Z, for whom digital media and technology play a crucial role and for whom these technologies are positively correlated with sustainability and its overall perception. Implications for policies and practices for emerging country governments are provided.

This article approaches the possibilities of photo elicitation as a technique for social research in the landscape of technology-mediated instantaneous interpersonal communication.

This case study, which involved persons with prison experience in the process of returning to the community, demonstrates how participant-generated photographs made with mobile handheld electronic devices and the meanings participants have attached to them allowed the research to take a co-creative turn.

The data analyzed show the potential of photo elicitation to build a link between researcher and researched that empowers the latter with agency in designing the results and also throughout the research process as a whole, thus allowing the former to reach a deeper level of understanding of the research participants' social reality.

The research conducted showcases the possibilities of this technique to approach the field of emotions from the ethnography and how they can build knowledge – especially in the work with vulnerable populations in vulnerable contexts – and generate new categories of analysis.

Motivated by recent research indicating that the operational performance of an enterprise can be enhanced by building a supporting data-driven environment in which to operate, this paper presents a simulation framework that enables an examination of the effects of applying smart manufacturing principles to conventional production systems, intending to transition to digital platforms.

To investigate the extent to which conventional production systems can be transformed into novel data-driven environments, the well-known constant work-in-process (CONWIP) production systems and considered production sequencing assignments in flowshops were studied. As a result, a novel data-driven priority heuristic, Net-CONWIP was designed and studied, based on the ability to collect real-time information about customer demand and work-in-process inventory, which was applied as part of a distributed and decentralised production sequencing analysis. Application of heuristics like the Net-CONWIP is only possible through the ability to collect and use real-time data offered by a data-driven system. A four-stage application framework to assist practitioners in applying the proposed model was created.

To assess the robustness of the Net-CONWIP heuristic under the simultaneous effects of different levels of demand, its different levels of variability and the presence of bottlenecks, the performance of Net-CONWIP with conventional CONWIP systems that use first come, first served priority rule was compared. The results show that the Net-CONWIP priority rule significantly reduced customer wait time in all cases relative to FCFS.

Previous research suggests there is considerable value in creating data-driven environments. This study provides a simulation framework that guides the construction of a digital transformation environment. The suggested framework facilitates the inclusion and analysis of relevant smart manufacturing principles in production systems and enables the design and testing of new heuristics that employ real-time data to improve operational performance. An approach that can guide the structuring of data-driven environments in production systems is currently lacking. This paper bridges this gap by proposing a framework to facilitate the design of digital transformation activities, explore their impact on production systems and improve their operational performance.

Several inferential procedures are advocated in the literature. The most commonly used techniques are the frequentist and the Bayesian inferential procedures. Bayesian methods afford inferences based on small data sets and are especially useful in studies with limited data availability. Bayesian approaches also help incorporate prior knowledge, especially subjective knowledge, into predictions. Considering the increasing difficulty in data acquisition, the application of Bayesian techniques can be hugely beneficial to managers, especially in analysing limited data situations like a study of expert opinion. Another factor constraining the broader application of Bayesian statistics in business was computational power requirements and the availability of appropriate analytical tools. However, with the increase in computational power, connectivity and the development of appropriate software programmes, Bayesian applications have become more attractive. This chapter attempts to unravel the applications of the Bayesian inferential procedure in marketing management.

Despite a large amount of BIM data at the handover stage, it is still difficult to identify and effectively isolate valuable construction supply chain (CSC) data that need to be reliably handed over for operation. Moreover, the role of reconciling disparate data is usually played by one party. The integration of blockchain and BIM is a plausible framework for building a reliable digital asset lifecycle. This paper proposes a BIM single source of truth (BIMSSoT) data model using blockchain for ensuring a reliable CSC data delivery.

This paper utilises a blended methodology, the foundation of which is ingrained in business and management research with elements of information and communication technology (ICT) research wherever required. Knowledge elicitation case studies utilising novel interventions such as a data flow diagram (DFD), taxonomy and entity-relationship diagram (ERD) were used in this paper to develop the BIMSSoT data model. The model was validated using an expert forum, and its technological feasibility was established by developing a proof of concept.

The practical contribution of this research leads to the progression of BIM towards digital engineering to go beyond object-based 3D modelling by building structured and reliable datasets, transitioning from project-centric records to a digital ecosystem of linked databases by utilizing blockchain's potential for ensuring trusted data.

To the best of the author's knowledge, prior to this paper, no research had investigated a detailed data model development leveraging blockchain and BIM to integrate an immutable and complete record of CSC data as another dimension of BIM for operations.

The purpose of this study is threefold: firstly, to compare Pakistani and French consumers’ perceptions of well-being; secondly, to investigate how consumers in both countries relate to food; and thirdly, to assess whether they associate food with well-being.

Thirty participants (15 French and 15 Pakistani) between the ages of 24 and 35 were interviewed, using convenience and snow bowling sampling. Data triangulation was performed by combining three qualitative techniques, word association, photo-elicitation-based interviewing and open-ended questions to explore consumer perceptions of well-being, food and food well-being.

The study’s findings suggest that well-being is a broad concept in which food is an ingredient. Food and well-being share common elements, and food well-being can be defined as an individual’s psychological, physical, social and societal relationship with food ascribed by affordability and food literacy.

Pleasure, sharing and respect emerged as dimensions of food well-being that can be applied to transfigure consumer behaviour and reduce over-consumption, food waste and hunger. The dimensions of well-being and food were explored for both countries to understand their cultural nuances and determine the influence of food on well-being. This comparative analysis will help researchers understand consumers’ preferences for food in various aspects from two regions. This study can potentially contribute to scale development in food and well-being, which can help researchers measure the effects of food and well-being in different sectors of the economy, particularly in health care. The most aspiring aspect of the current research is the insights unveiled during interactions with research participants, which will help develop consumer baseline feelings.

Brands are relevant to multiple stakeholders and, as such, can have multiple meanings. Drawing on branding and stakeholder marketing theory, the purpose of this study was to provide in-depth insights into knowledge dynamics related to the so-called family business brand across different stakeholder perspectives.

This study combines advanced brand concept mapping (BCM) with a scenario technique to graphically capture consumers’ and jobseekers’ brand knowledge related to the family business concept in the form of association networks.

Findings show both a shared core meaning (e.g. associations such as “tradition” or “owner-managed”) and stakeholder-specific associations (e.g. consumer perspective: “high product quality,” “handmade”; jobseeker perspective: “appreciation within the company,” “outdated”). Significantly, the results reveal detailed insights into cross-stakeholder knowledge dynamics regarding the associations’ interconnections, strength and favorability.

By combining BCM with a scenario technique, this study adopts an approach that is aimed at better understanding and comparing brand knowledge with respect to the family business brand across multiple stakeholder perspectives. Given the prevalence of family businesses, this research enhances the theoretical and practical understanding of a branding resource that is often available but rarely exploited.

This study aims to explore how brands use brand personification techniques in real-time marketing on social media, particularly Twitter, and examine how these techniques impact consumer engagement, moderated by brand-event congruence levels.

Data included 464 tweets posted by 95 brands around three large events in 2019. The types of brand personification techniques and the level of brand-event congruence applied by the tweets were content-analyzed, and regression analyses were conducted to examine their linkages to consumer engagement metrics.

Results confirmed the use of diverse personification techniques in brands’ real-time marketing tweets as in the previous literature. The study also revealed a new personification technique, tacit expression, not reported in previous literature. The study also showed that the overall effectiveness of multimedia-based (vs caption-based) personification techniques in increasing consumer engagement on social media was greater, but their relative effectiveness varied depending on whether or not the event was functionally congruent with the brand.

The findings offer valuable suggestions to brand managers regarding prioritizing brand personification techniques and aligning brands’ social media marketing with real-time events to maximize the effectiveness of real-time marketing in boosting consumer engagement.

This research offers insights into the dynamic effects of different brand personification techniques in the new context of real-time marketing, extending the scope of literature on brand personification and anthropomorphism. The revelation of a new type of brand personification not captured in the extant literature is also a significant contribution.

In this article, we discuss an innovative audience research methodology developed for the AHRC-funded “Beyond the Multiplex: Audiences for Specialised Film in English Regions” project (BtM). The project combines a computational ontology with a mixed-methods approach drawn from both the social sciences and the humanities, enabling research to be conducted both at scale and in depth, producing complex relational analyses of audiences. BtM aims to understand how we might enable a wide range of audiences to participate in a more diverse film culture, and embrace the wealth of films beyond the mainstream in order to optimise the cultural value of engaging with less familiar films. BtM collects data through a three-wave survey of film audience members’ practices, semi-structured interviews and film-elicitation groups with audience members alongside interviews with policy and industry experts, and analyses of key policy and industry documents. Bringing each of these datasets together within our ontology enables us to map relationships between them across a variety of different concerns. For instance, how cultural engagement in general relates to engagement with specialised films; how different audiences access and/or share films across different platforms and venues; how their engagement with those films enables them to make meaning and generate value; and how all of this is shaped by national and regional policy, film industry practices, and the decisions of cultural intermediaries across the fields of film production, distribution and exhibition. Alongside our analyses, the ontology enables us to produce data visualisations and a suite of analytical tools for audience development studies that stakeholders can use, ensuring the research has impact beyond the academy. This paper sets out our methodology for developing the BtM ontology, so that others may adapt it and develop their own ontologies from mixed-methods empirical data in their studies of other knowledge domains.