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Technology is revolutionizing the management logic of service systems. The increasing use of artificial intelligence (AI), in particular, is challenging interaction between humans and machines changing the service systems’ value co-creation configurations and logic. To envision possible future scenarios, this paper aims to reflect upon how the humans’ use of AI technology can impact value co-creation.

The study is developed, at a conceptual level, using selected elements from managerial and marketing theoretical frameworks interested in value co-creation – Service-Dominant Logic, Service Science and Viable Systems Approach (VSA) – used as interpretative tools to reframe value co-creation in the digital age.

The interpretative approach adopted and, in particular, the new VSA notion of Intelligence Augmentation (IA), in the perspective of the information variety model, shed new light on value co-creation in the digital age framing a possible “IA effect” that can empower value co-creation in complex decision-making contexts.

The study provides insights useful in the design and management of service systems suggesting a rethinking of the view of AI as a means for mainly increasing the smartness of service systems and a new focus on the enhancement of the human resources contribution to make the service systems wiser.

The paper provides a refocused interpretative view of the interaction between humans and AI that looks at a possible positive impact of the use of AI on humans in terms of augmented decision-making capabilities in conditions of complexity.

Deficiencies or imbalances in dietary fat intake may influence on mental and neurological functions of children with autism spectrum disorders (ASD). This study aims to compare body mass index (BMI) and the amount of fatty acids intake in the autistic patients with the comparison group.

This case-control was carried out on 200 randomly selected children from 5 to 15 years old (100 autistic patients as the case group and 100 healthy children as the comparison group) in Tehran, Iran. The food frequency questionnaire (FFQ) was used to assess the intake of calorie, macronutrients and different types of dietary fatty acids including saturated fatty acids (SFA), monounsaturated fatty acids (MUFAs), poly unsaturated fatty acids (PUFAs), linoleic acid (LA), α-Linolenic acid (ALA), eicosapentaenoic acid (EPA), docosahexaenoic acid (DHA) and trans fatty acids.

The autistic patients had higher BMI, birth weight and mother’s BMI compared to the comparison group (All p < 0.01). No significant difference was found in the amount of dietary calorie, protein, carbohydrate and total fat intake between two groups. The risk of ASD was associated with higher intake of MUFAs (OR: 3.18, CI%:1.13–4.56, p = 0.04), PUFAs (OR: 4.12, CI95%: 2.01–6.25, p < 0.01) and LA (OR: 4.76, CI95%: 1.34–14.32, p < 0.01).

The autistic children had higher BMI and higher intake of unsaturated fatty acids except for omega-3 fatty acids. Further longitudinal studies are warranted.

This paper aims to empirically analyse the relationship between the business model and the evolution of employment during the Great Recession, based on data from 75 industrial companies in the Corredor del Henares in Guadalajara, a reference area for being one of the fastest growing economic and business areas in Spain in recent decades.

The concept of the business model has been incorporated into organizational theory and practice over the last 25 years and continues to attract the interest of the academic and business community. The most recent research found in the literature has confirmed the relationship between business model and business performance, being directly connected to business performance and, therefore, to the creation of employment. However, the conclusions of the available studies are not directly scalable, as they refer to a specific sector or market.

The result confirms the positive impact of the business model on results and specifically, that talent management, through the value proposition and technology, has an impact on improving business performance. The study specifically confirms that talent integrated in organizations has an impact on the performance through a solid value proposition, scalable and adaptable to changes in the environment and whose transformation must be led by the top management. Talent integrates key partners and considers corporate social responsibility, sustainability, security and transparency as key factors in its management.

Thus, providing new and relevant information for research and business practice, and its conclusions are generalisable thanks to the multi-sector and multi-territorial nature of the sample selected.

This systematic literature review presents the state of the field of fashion and crisis communication. The quantitative coding offers insight into dominant and emergent themes in one of the most crisis-prone industries. This review also offers a framework for future research.

This study uses a systematic literature review approach. 205 academic articles were gathered in total using the search term “fashion industry crisis”. Subsequently, they were quantitatively coded using the Diers-Lawson (2016) Crisis Communication Code Book.

Findings show an increase in the fashion industry crisis with clear emergent themes such as sustainability, emphasising the truly global and multidisciplinary nature of the industry. Findings also reveal a genuine lack of theoretical grounding, with over 80% of the articles coded using no crisis communication theory. The findings also suggest value co-creation ought to be a priority for this agenda moving forward, as it overlaps with emerging themes and is a practical tool and concept to support crisis prevention and management through an extension of the Stakeholder Relationship Model (SRM) Model.

As a largely under-researched area in crisis communication, the findings present a new opportunity to explore fashion within its context and contribute. At this point, the research field is lacking, and there is room for theory testing and hypothesis building. The findings and themes from the research present a development of the original SRM model, SRM Val-Co.

As well as research implications, the proposed framework provides practical solutions for the future of the fashion industry.

As a largely under-researched area in crisis communication, the findings demonstrate a new opportunity to explore fashion within its context and contribute because there is a dearth of research and a lack of theoretical development. Therefore, the proposed framework provides practical solutions for the fashion industry’s future. The findings and themes from the research present a development of the original SRM model, SRM Val-Co.

This study seeks to enhance productivity, motivation and well-being of workers by improving decision-making processes. Using inner knowledge management (IKM), this study aims to identify, manage and transform unconscious beliefs and negative emotions that limit decision-making processes.

The methodology used is empirical research, analyzing multiple cases qualitatively and using the T-test statistical model to analyze the hypotheses. The study tests the relation between different limiting beliefs and negative emotions that influence decision-making processes.

This study shows that IKM is positively related to the productivity, motivation and well-being of workers.

The study is limited to workers who are mentally healthy, who work in teams and who seek professional help to achieve their goals.

The results indicate that there is a lot of potential to be explored applying IKM in companies and organizations. Specifically, this study proves that there are several inner knowledge assets that constrain the workers’ potential and therefore affect the efficiency of businesses.

The results have strong implications for how companies and organizations can create great value for themselves and their workers.

To the best of the authors’ knowledge, this is the first data-based study using an IKM model. The importance of this study opens the door to further exploration of the effects on IKM on productivity, motivation and the general well-being of workers.

This paper aims to probe the prevailing belief that engaging in innovative work behavior (IWB) will invariably lead to favorable outcomes. To do so, the paper integrates followership theory and cognitive dissonance theory to investigate the connection between employees’ IWB and despotic leadership, and the mediating role of interpersonal conflict with the supervisor in this connection. Moreover, the moderating impact of the supervisor’s dispositional resistance to change trait on the direct and indirect relationship between IWB and despotic leadership is explored.

The data were collected through a multi-wave survey of 350 employees and 81 supervisors working in 81 public schools.

The findings show that IWB has a positive and significant relationship with despotic leadership, and this relationship is mediated by interpersonal conflict with the supervisor.

To the best of the authors’ knowledge, this is the first study that examines the link between IWB and despotic leadership via interpersonal/dyadic conflict and explores the moderating effect of leadership dispositional resistance to change trait in this indirect relationship.

The purpose of this paper is to determine the most efficient hotels in the Indian hotel industry, the competitive positioning of these hotels, and the factors that affect their efficiency change.

This study conducts a two-stage analysis and uses data envelopment analysis (DEA) and Global Malmquist productivity index (MPI) approach in the first stage to calculate the managerial performance of a panel of 63 Indian hotels in 2019–2020 and their efficiency change from 2009–2010 to 2019–2020. Bootstrapped generalized least square (GLS) approach is applied in the second stage to evaluate the impact of contextual variables on efficiency change.

Using the results of the first stage analysis, the authors categorized the 63 Indian hotels into 7 distinct clusters. These clusters represent different levels of competitiveness and pace of growth. The GLS regression reveals a U-shaped relationship between hotel size and efficiency change and a negative relationship between pro social investments and efficiency.

This is the first study in the hotel industry that has used global MPI as a measure of efficiency change in the first stage and GLS in the second stage. In the Indian context, to the best of authors’ knowledge, no such study exists.

This study aims to evaluate the key factors affecting the behavioural intention of urban tourists towards visiting national parks by integrating the theory of planned behaviour (TPB) and expectancy theory (ET).

Data were collected from urban tourists using an online questionnaire developed through Google forms. A total of 489 valid online questionnaires were considered for this study. The proposed research model was empirically evaluated using the structural equation modelling method.

According to the results of this research, TPB constructs are significantly and positively associated with the behavioural intention of urban tourists towards visiting national parks in India and out of ET constructs, only expectancy and valence are significantly and positively associated with behavioural intention while instrumentality does not.

This study manifests the behaviour of urban tourists towards national parks and contributes to academics by incorporating existing literature. The findings of this study also help policymakers in formulating innovative strategies for national parks. It presents an integrated framework that lays the platform for a new study domain on urban tourists' intentions to visit national parks, which will be useful to urban managers, officials and the tourism sector. Furthermore, as the scope of this study is confined to assessing the intentions of urban tourists toward visiting national parks, it is difficult to generalize the findings.

To the best of the authors' knowledge, this is the first research of its kind to provide an understanding of the behavioural intention of urban tourists towards visiting the national parks in India by optimizing the TPB and ET.

In response, this study developed a mathematical and computational method, through spatial configurations with justified plan graph (JPG), drawn from Space Syntax to extract essential information of the spatial topology of 13 valuable traditional courtyard houses located in Toon historical city of Iran.

Historical vernacular housing has always been designed to incorporate and reflect the local lifestyle and cultural conditions. “Courtyard” is a fundamental part of traditional Iranian houses. This traditional building type includes a walled boundary and a complex of open, semi-enclosed and enclosed spaces. This study investigates the traditional houses in Toon historical town. Toon is one of the ancient towns in southeast Iran, including old courtyard houses in its heritage context. The spatial influence of the courtyard contributes to the formation of this famous architectural type.

The results show the remarkable impact of this space on dominating the plan of traditional Toon houses configuration compared to other spaces in all cases. Furthermore, spatial accessibility has changed over time, and the Safavid period had a higher level of integration and lower level of accessibility (mean i = 7.03) rather than the Qajar period (mean i = 6.34); also, privacy has decreased progressively.

The knowledge of characteristics of this historical architecture needs to be gathered for the preservation and conservation of the built heritage. Hence, the principle behind traditional Iranian courtyards was investigated to recognize the difference between the spatial influence of the courtyard and other spaces and the changes in the courtyard over time.

Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.

To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.

The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.

The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.