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This study contributes to the scant research on dealcoholised wine from a consumer behaviour perspective by providing insight and reporting on the attributes that South African Generation Y consumers prefer when purchasing dealcoholised wine.

A two-phased research approach was adopted, involving a main quantitative phase, preceded by a qualitative phase. Data were gathered from 626 South African Generation Y respondents by means of a questionnaire. The best–worst scaling method was applied to 13 selected dealcoholised wine attributes, to measure the level of importance of each attribute. To gain more insight on the data, the best-worst scaling scores were further standardised to a probabilistic ratio scale.

“Taste”, “price” and “I have tried it before” were the most important attributes that respondents considered when purchasing dealcoholised wine. Furthermore, “taste” was by far the most important of all the attributes. The attributes of “back label”, “attractive front label” and “brand name” were identified as the least important by the respondents, suggesting that they did not consider the visual elements of a bottle of dealcoholised wine as particularly important in their purchasing decision.

The findings of this pioneering study contribute to the lack of knowledge about dealcoholised wine from a consumer behaviour and marketing perspective, and provide insights and strategies that can be used by stakeholders to enhance the dealcoholised wine market in South Africa.

The literature on economic forecasting, is showing an increase in criticism, of the inaccuracy of forecasts, with major implications for economic, and fiscal policymaking. Forecasts are subject to the systemic uncertainty of human systems, considerable event-driven uncertainty, and show biases towards optimistic growth paths. The purpose of this study is to consider approaches to improve economic foresight.

This study describes the practice of economic foresight as evolving in two separate, non-overlapping branches, short-term economic forecasting, and long-term scenario analysis of development, the latter found in studies of climate change and sustainability. The unique case of Ireland is considered, a country that has experienced both steep growth and deep troughs, with uncertainty that has confounded forecasting. The challenges facing forecasts are discussed, with brief review of the drivers of growth, and of long-term economic scenarios in the global literature.

Economic forecasting seeks to manage uncertainty by improving the accuracy of quantitative point forecasts, and related models. Yet, systematic forecast failures remain, and the economy defies prediction, even in the near-term. In contrast, long-term scenario analysis eschews forecasts in favour of a set of plausible or possible alternative scenarios. Using alternative scenarios is a response to the irreducible uncertainty of complex systems, with sophisticated approaches employed to integrate qualitative and quantitative insights.

To support economic and fiscal policymaking, it is necessary support advancement in approaches to economic foresight, to improve handling of uncertainty and related risk.

While European Union Regulation (EC) 1466/97 mandates pursuit of improved accuracy, in short-term economic forecasts, there is now a case for implementing advanced foresight approaches, for improved analysis, and more robust decision-making.

Building economic resilience and adaptability, as part of a sustainable future, requires both long-term strategic planning, and short-term policy. A 21st century policymaking process can be better supported by analysis of alternative scenarios.

To the best of the authors’ knowledge, the article is original in considering the application of scenario foresight approaches, in economic forecasting. The study has value in improving the baseline forecast methods, that are fundamental to contemporary economics, and in bringing the field of economics into the heart of foresight.

Disaster management and humanitarian logistics (HT) play crucial roles in large-scale events such as earthquakes, floods, hurricanes and tsunamis. Well-organized disaster response is crucial for effectively managing medical centres, staff allocation and casualty distribution during emergencies. To address this issue, this study aims to introduce a multi-objective stochastic programming model to enhance disaster preparedness and response, focusing on the critical first 72 h after earthquakes. The purpose is to optimize the allocation of resources, temporary medical centres and medical staff to save lives effectively.

This study uses stochastic programming-based dynamic modelling and a discrete-time Markov Chain to address uncertainty. The model considers potential road and hospital damage and distance limits and introduces an a-reliability level for untreated casualties. It divides the initial 72 h into four periods to capture earthquake dynamics.

Using a real case study in Istanbul’s Kartal district, the model’s effectiveness is demonstrated for earthquake scenarios. Key insights include optimal medical centre locations, required capacities, necessary medical staff and casualty allocation strategies, all vital for efficient disaster response within the critical first 72 h.

This study innovates by integrating stochastic programming and dynamic modelling to tackle post-disaster medical response. The use of a Markov Chain for uncertain health conditions and focus on the immediate aftermath of earthquakes offer practical value. By optimizing resource allocation amid uncertainties, the study contributes significantly to disaster management and HT research.

Factors like bid price, submission time, and number of bidders influence the procurement process in public projects. These factors and the award criteria may impact the project’s financial compliance. Predicting budget compliance in construction projects has been traditionally challenging, but Machine Learning (ML) techniques have revolutionised estimations.

In this study, Portuguese Public Procurement Data (PPPData) was utilised as the model’s input. Notably, this dataset exhibited a substantial imbalance in the target feature. To address this issue, the study evaluated three distinct data balancing techniques: oversampling, undersampling, and the SMOTE method. Next, a comprehensive feature selection process was conducted, leading to the testing of five different algorithms for forecasting budget compliance. Finally, a secondary test was conducted, refining the features to include only those elements that procurement technicians can modify while also considering the two most accurate predictors identified in the previous test.

The findings indicate that employing the SMOTE method on the scraped data can achieve a balanced dataset. Furthermore, the results demonstrate that the Adam ANN algorithm outperformed others, boasting a precision rate of 68.1%.

The model can aid procurement technicians during the tendering phase by using historical data and analogous projects to predict performance.

Although the study reveals that ML algorithms cannot accurately predict budget compliance using procurement data, they can still provide project owners with insights into the most suitable criteria, aiding decision-making. Further research should assess the model’s impact and capacity within the procurement workflow.

Previous research predominantly focused on forecasting budgets by leveraging data from the private construction execution phase. While some investigations incorporated procurement data, this study distinguishes itself by using an imbalanced dataset and anticipating compliance rather than predicting budgetary figures. The model predicts budget compliance by analysing qualitative and quantitative characteristics of public project contracts. The research paper explores various model architectures and data treatment techniques to develop a model to assist the Client in tender definition.

Quality management (QM) can support organisations in contributing to sustainable development. As a result of an expanding focus from customers towards stakeholders within QM, the perspectives to consider multiply. Understanding how practices and tools for process management are specifically affected by this increase in perspectives is key to creating the right conditions for improvement initiatives that support sustainable development.

This paper constructs a typology wherein the use of process management practices and tools is described in nine distinguished system contexts. Inductive discrimination is used to differentiate the system contexts and different use cases for process practices and tools.

Using the system of systems grid (SOSG), mainstream business process management (BPM) practices are positioned in a simple unitary context, whilst sustainability challenges also involve more complex contexts. Addressing these challenges requires integrating new tools and methods from paradigms outside of traditional functionalist business process management practices.

This paper highlights the necessity to consider system contexts when developing feasible practices and tools for effective process management.

Practical implications are that quality practitioners aiming to exploit the potential in process management to support sustainability get support for planning and conducting process improvement initiatives aiming to consider several stakeholder perspectives.

This paper presents a new typology for understanding the context of QM process initiatives and BPM in light of a contemporary sustainability focus.

This paper explores the Adoption of Technological Innovation (ATI) in the healthcare industry. It investigates how the literature has evolved, and what are the emerging innovation dimensions in the healthcare industry adoption studies.

We followed a mixed-method approach combining bibliometric methods and topic modeling, with 57 papers being deeply analyzed.

Our results identify three latent topics. The first one is related to the digitalization in healthcare with a specific focus on the COVID-19 pandemic. The second one groups up the word combinations dealing with the research models and their constructs. The third one refers to the healthcare systems/professionals and their resistance to ATI.

The study’s sample selection focused on scientific journals included in the Academic Journal Guide and in the FT Research Rank. However, the paper identifies trends that offer managerial insights for stakeholders in the healthcare industry.

ATI has the potential to revolutionize the health service delivery system and to decentralize services traditionally provided in hospitals or medical centers. All this would contribute to a reduction in waiting lists and the provision of proximity services.

The originality of the paper lies in the combination of two methods: bibliometric analysis and topic modeling. This approach allowed us to understand the ATI evolutions in the healthcare industry.

The purpose of this paper is to develop a methodology for shaping the tourist spatial identity of the city and to take advantage of it to discover alternative urban outdoor spaces. As the number of indoor visitors has been limited due to the COVID-19 pandemic, open urban areas such as streets, squares and parks have become more important tourist locations.

The assessment methodology consists of two basic steps. In the first step, the authors look for places or points that are carriers of spatial identity. For this purpose, the method of mental mapping is used. In the second step, statistical methods are used to evaluate the spatial suitability for the most common tourist activities. To obtain a holistic picture, a temporal component is included.

The application of the methodology is presented in the form of a case study. The obtained research results provide an insight into the spatial situation of the city of Maribor (Slovenia, Europe). Tourist spatial identity of a city depends on time. Based on the value of spatial sensitivity indicator and the suitability of activities, it is possible to adapt the tourist offer to the temporal component.

To the best of the authors’ knowledge, this is an original perspective on the spatial identity of tourists. The presented approach could be integrated as a good practice in any other city worldwide. It supports the identification of suitable outdoor tourist places that are memorable, cosy, multifunctional and can be recommended by city guides (mobile or printed books). Every city has many hidden gems that tourists have yet to discover.

The purpose of this paper is to investigate how the pandemic affects tenants’ response to their lease obligations. This paper commences with examining the adopted tenant selection criteria during the COVID-19 pandemic. Then, this paper statistically tests if there is a relationship between selection criteria and response on whether the pandemic has effects or not. Then, this paper investigates the specific areas of impact on tenants’ ability to adequately keep to lease agreements in the Nigerian rental market. Finally, this paper proceeds to confirm if there is a relationship between selection criteria and the aspects of tenants’ deficiencies in rental obligations because of COVID-19.

Survey data, backed with interviews, is elicited from practicing estate surveyors and valuers and licensed property managers in Lagos, the largest property market in Nigeria and sub-Sahara Africa. Policy solutions and implications were solicited from personnel at the ministry of housing and senior professionals in the property sector. Data were analyzed using descriptive statistics, factor analysis and computer-aided qualitative data analysis, Atlas.ti.

Tenant’s health status is now accorded a priority together with others. Numbers of tenants are challenged with keeping to the prompt-rent-payment rule. Other areas of slight breaches included livestock rearing, subletting, alteration and repair covenants. Except for tenant reputation and tenant family size, there was no significant relationship between tenant’s health status consideration and the COVID-19 effect on tenant non-compliance with lease obligation. Tenants’ non-compliance with tenancy obligations has a connection with the tenants’ affordability, reputation, ability to sign an undertaking and health conditions during the pandemic. This paper recommends rental housing policy review.

It is recommended that the rental policy should be reviewed to give room for rental allowance or palliatives, private rental market regulation, exploration of the national housing fund and, if possible, social housing adoption policy in Nigeria.

This paper draws policymakers’ attention to the need to prepare for the future safety net that caters to citizenry welfare in challenging times.

This paper seeks to understand users' perceptions of their experiences in mobile applications (apps) with gamified loyalty programs (GLPs) that use rewards as the primary engagement vehicle. The research focuses particularly on the motivations to further interact with GLPs and the motivational changes occurring after successive interactions.

The authors conducted weekly open qualitative interviews over a month (four rounds of interviews) with five Portuguese active users of the mobile app Yorn Shake It, from Vodafone, which is a relevant case study to illustrate GLPs in mobile apps.

Participants' motivations to interact with the mentioned GLP are shaped by the reward incentive and users' perceptions of the gamified interactive experience. Motivational changes occur regardless of the presence of external contingencies and depend on contextual changes or perceived results of the gamified experience. This means that rewards also satisfy intrinsic needs, but users may remain connected to the system as long as fun experiences are provided without exhausting perceptions. Also, motivation may turn to reward contingencies when the challenge becomes boring.

This is the first qualitative study explaining the perceptions of gamified experiences after continued participation, extending knowledge about the importance of a fair balance between the value and achievement of rewards and the entertainment of the challenge provided after continued exposure. The findings provide insights to GLP marketing managers and developers to better engage target audiences according to their needs and past experience, creating levels of challenges and fair rewards to maintain motivation and prevent abandonment after continued exposure.

This study operationalizes risks in stakeholder dialog (SD). It conceptualizes SD as co-produced organizational discourse and examines the capacities of organizers' and stakeholders' practices to create a shared understanding of an organization’s risks to their mutual benefit. The meetings and online forum of a German public service media (PSM) organization were used as a case study.

The authors applied corpus-driven linguistic discourse analysis (topic modeling) to analyze citizens' (n = 2,452) forum posts (n = 14,744). Conversation analysis was used to examine video-recorded online meetings.

Organizers suspended actors' reciprocity in meetings. In the forums, topics emerged autonomously. Citizens' articulation of their identities was more diverse than the categories the organizer provided, and organizers did not respond to the autonomous emergence of contextualizations of citizens' perceptions of PSM performance in relation to their identities. The results suggest that risks arise from interactionally achieved occasions that prevent reasoned agreement and from actors' practices, which constituted autonomous discursive formations of topics and identities in the forums.

This study disentangles actors' practices, mutuality orientation and risk enactment during SD. It advances the methodological knowledge of strategic communication research on SD, utilizing social constructivist research methods to examine the contingencies of organization-stakeholder interaction in SD.