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Previous studies have demonstrated that an autonomy-supportive supervision style is associated with improved well-being and positive behaviours for supervisees. However, autonomy-supportive training (AST) has yet to be tailored to suit supervisors in low-skilled occupations for whom traditional pedagogical approaches may be inappropriate. The purpose of this paper is to describe the development and preliminary evaluation of AST for these supervisors, using self-determination theory (SDT) and andragogical principles of adult learning.

SDT and andragogical principles were systematically integrated to develop (a 3 h) AST programme. The training sessions were trialled with 11 first-line supervisors in New Zealand as a preliminary evaluation of AST. The evaluation used open-ended questions following Kirkpatrick’s evaluation model and incorporated the trainer’s reflections.

Supervisors found AST relevant, easy to understand and suited to their approach to learning. Trainer’s reflections also provided insight into the challenges in conducting such training for supervisors in low-skilled occupations and the article makes suggestions to address these challenges.

AST can be successfully tailored to first-line supervisors, indicating that an autonomy-supportive style of leadership is relevant for those employed in low-skilled occupations. This initial evaluation provides a foundation for future studies to conduct higher-level assessment of AST.

AST can be utilised to provide first-line supervisors with access to improved leadership development opportunities. Challenges of conducting this kind of training programme in a context of low-skilled occupations are addressed and recommendations made for organisations and trainers.

This study is novel as it demonstrates the development of AST, a leadership skills training, tailored to suit the needs of an understudied group, supervisors in low-skilled occupations.

This paper aims to investigate the interactive effect of Gestalt versus non‐Gestalt situations, and arousal seeking tendency (AST) on customers' pleasure and arousal with matching color and music to hotel bars and hotel guest rooms; thereby providing guidance for service providers.

This is an experimental design study with four treatments. Fictitious hotel bar and guest room video clips were created with the appropriate manipulation of color schemes and music as independent variables. After the video clip was shown, subjects were asked to complete a survey instrument. The hypothesized model was then tested.

The results showed that the interactive effect of Gestalt versus non‐Gestalt, and AST on an individual's pleasure and arousal are both positive and statistically significant. As an individual's AST increases, both the arousal score and pleasure score increased in Gestalt situations (dynamic bar and tranquil guest room) and decreased in non‐Gestalt situations (tranquil bar and dynamic guest room).

Only jazz music and a specific type of hotel bar and hotel guest room settings with a limited target market were utilized. Similarly, the color schemes that were included were the two extremes (dynamic and tranquil). Results can be generalized to other similar settings only with caution.

Hospitality firms should design spaces taking into account the holistic or Gestalt effect of objective elements of a servicescape. Managers should understand that individual uses of a servicescape and reactions to objective servicescape elements will be different depending on a specific type of servicescape.

No research has been done investigating the effects of the color and music combined in two distinct service settings. The value of assessing effects of different settings is demonstrated.

Manufacturing small and medium-sized enterprises (SMEs) are heading towards smart manufacturing despite growing challenges caused by globalisation and rapid technological advancement. These SMEs, particularly textile SMEs of Bangladesh, also face challenges in implementing sustainability and organisational ambidexterity (OA) due to resource constraints and limitations of conventional leadership styles. Adopting paradoxical leadership (PL) and entrepreneurial bricolage (EB) is important to overcome the challenges. However, these dynamics are less explored in academia, especially in the Bangladeshi textile SMEs context. Hence, the purpose of this study is to investigate the influence of the adoption of smart technologies (ASTs), PL and OA, EB on sustainable performance (SP) of textile SMEs in Bangladesh.

A cross-sectional and primary quantitative survey was conducted. Data from 361 textile SMEs were collected using a structured self-administrated questionnaire and analysed by partial least square structural equation modelling (PLS-SEM).

The statistical outcome confirms that ASTs and PL significantly influence SP and OA. OA plays a significant mediating role for PL and is insignificant for ASTs, and EB significantly moderates among ASTs, PL and SP.

As this study is cross-sectional and focussed on a single city (Dhaka, Bangladesh), conducting longitudinal studies and considering other parts of the country can provide exciting findings.

This research provides valuable insights for policymakers, management and textile SMEs in developing and developed countries. By adopting unique and innovative OA, PL and EB approaches, manufacturing SMEs, especially textile companies, can be more sustainable.

This study has a novel, pioneering contribution, as it empirically validates the role of multiple constructs such as AST, PL, OA and EB towards SP in the context of textile SMEs in a developing country like Bangladesh.

Active school travel (AST) programmes aim to change commuting behaviour to improve children's physical and mental health. However, very limited health education programmes for children use segmentation to create tailored solutions that understand the specific characteristics of each group of children and their caregivers in order to yield better results. The aim of this study is to use a statistical segmentation analysis (two-step cluster analysis) to gain insights on the examination of specific groups to design future health education interventions and campaigns that can improve children's health.

Guided by the Ecological and Cognitive Active Commuting (ECAC) framework, a market segmentation analysis was performed. An online survey was designed to collect data from caregivers of children between 5 and 12 years attending school and responsible for taking the child to and/or from school in Victoria and Queensland, Australia. Using 3,082 responses collected from Australian caregivers of primary school children, a two-step cluster analysis was performed.

Analysis revealed the most important variables for group formation were previous child walking behaviour, distance from school and caregiver income. Perceived risk of the physical environment was the most important psychographic segmentation variable for group formation, followed by social norms. Four distinct groups with different characteristics were identified from the analysis.

This is the first study that applies the ECAC framework to perform market segmentation in the AST context. Results revealed four market segments that demand different tailored solutions. Findings shed light on how to better design AST interventions and campaigns to promote children's health using segmentation techniques.

Sports tourism has gained much attention in recent decades due to its socio-economic and environmental impact on destinations. This study at first examines travel motives that might trigger participation in active sports tourism (AST). Further, it compares these travel motives and their impact on participation intention in AST (between India and Poland).

Data were collected online through a self-administered questionnaire in both countries (N = 273 in India and N = 255 in Poland). Descriptive data were analyzed using SPSS statistics 24, and SPSS AMOS 25 was used for testing the measurement model and multi-group analysis.

The results show that in both countries, participants are motivated mainly by travel exploration, social bonding, and stress relief, which are the primary travel motives commonly associated with tourism. However, the significance of these motives varies across both nations. Interestingly, active sports tourists are not motivated by physical strength, self-enhancement, and social recognition.

The study presents a framework to discuss travel motives in Active Sports Tourism (AST). It also describes the motives that influence Indians and Polish citizens' participation in active sports tourism.

Reviews the literature pertaining to the implementation of the advanced skills teacher (AST) category. Presents initial data from a current research programme which is investigating the introduction of the AST category into the education systems of Victoria and South Australia. Research involves a study of the implementation of the AST category in two primary schools, interviews with senior administrators and perusal of memoranda and other documents relating to AST introduction. Discusses perceptions of teachers on work and skills with reference to whether the teacher′s skill is an art or a craft and the changing importance of skill. The current scenario evident in education is a mix of deskilling, upgrading of skills and a maintenance of the existing skills.

GraphQL is a new Open API specification that allows clients to send queries and obtain data flexibly according to their needs. However, a high-complexity GraphQL query may lead to an excessive data volume of the query result, which causes problems such as resource overload of the API server. Therefore, this paper aims to address this issue by predicting the response data volume of a GraphQL query statement.

This paper proposes a GraphQL response data volume prediction approach based on Code2Vec and AutoML. First, a GraphQL query statement is transformed into a path collection of an abstract syntax tree based on the idea of Code2Vec, and then the query is aggregated into a vector with the fixed length. Finally, the response result data volume is predicted by a fully connected neural network. To further improve the prediction accuracy, the prediction results of embedded features are combined with the field features and summary features of the query statement to predict the final response data volume by the AutoML model.

Experiments on two public GraphQL API data sets, GitHub and Yelp, show that the accuracy of the proposed approach is 15.85% and 50.31% higher than existing GraphQL response volume prediction approaches based on machine learning techniques, respectively.

This paper proposes an approach that combines Code2Vec and AutoML for GraphQL query response data volume prediction with higher accuracy.

The purpose of this paper is to further adaptive structuration theory (AST) by associating technological appropriations with health information technology workarounds. The author argues that appropriating electronic health record (EHR) technology ironically – in a way other than it is designed to be used – and divergently across an organization results in enhanced perceptions of EHR technology and its implementation.

Data were collected from 345 healthcare employees in a single healthcare organization that was switching to EHRs from paper records. Two major constructs of AST – unfaithfulness and dissension in appropriation – were operationalized and analyzed using multivariate regressions to test the relationship between the type of appropriation and perceptions of EHR technology’s relative advantage and implementation success.

Results reveal that both ironic (unfaithful) technological appropriation and dissension in technological appropriation across the organization predicted employees’ perceptions of EHR’s relative advantage and perceptions of EHR implementation success. Furthermore, physicians are the least likely to perceive EHR’s relative advantage or EHR implementation success. These results exemplify that EHR workarounds are taking place and reaffirm AST’s principle that employees evolve technology to better suit their working environments and preferences.

The survey and scales used in this study further demonstrate that there are meaningful statistical measures to accompany the qualitative methods frequently used in the AST literature. In addition, this paper expands AST research by exploring the positive outcomes that follow ironic and divergent technology appropriations.

Evidence indicates that active school travel (AST) including walking can effectively lower levels of obesity among school-age children. Yet Queensland has been identified as one of the most inactive states in Australia where only 5 per cent of Years 1 and 5 children engaged in AST on a daily basis. The purpose of this paper is to explain walking to school behaviour among Queensland children by investigating the explanatory potential of the ecological and cognitive active commuting (ECAC) model.

An online survey of 537 carers in Queensland, Australia was conducted to collect data about demographics and the variables in the ECAC model. Structural equation modelling was used to analyse the ECAC model and the pathways between variables.

The results indicate that the ECAC model explained 53.4 per cent of the variance in walking to school. Social norms are the dominating factor in the model. Distance to school affects how the ECAC model works by moderating the associations among walking to school behaviours, perceived risks, and social norms.

Changing carers’ social norms and lowering the perceived risks they associate with walking to school should increase the incidence of walking to school in Queensland.

Although the ECAC model was proposed as a comprehensive framework to explain walking to school behaviour, to date, it has not been tested empirically. Informed by a modified ECAC framework this study aims to empirically explore the factors that may be preventing or facilitating Queensland children from walking to school.

The purpose of this study is to examine the underlying mechanisms of exploitative innovation and exploratory innovation between social media usage and organizational agility, and elucidate the moderating role of learning goal orientation (LGO) in the above relationships, based on adaptive structuration theory (AST).

Based on a multiple-respondent matched survey of 334 Chinese e-commerce firms, authors employed structural equation modeling to examine the correlations among social media usage, exploitative innovation, exploratory innovation and organizational agility. Hierarchical regression analysis was used to examine the moderating role of LGO.

This study's empirical findings demonstrate that exploitative innovation and exploratory innovation mediate the relationship between social media usage and organizational agility in different ways. Further, LGO positively moderates the relationship between social media usage for customer acquisition and exploratory innovation, as well as the relationship between social media usage for customer relationship and exploitative innovation.

Firms are advised to leverage different types of social media usage to facilitate exploitative innovation and exploratory innovation and promote organizational agility. In addition, LGO within a firm should be established to enhance the effects of social media usage on exploitative innovation and exploratory innovation.

This study adds to the literature on social media usage by proposing and examining exploitative innovation and exploratory innovation as explanatory mechanisms to facilitate organizational agility. This study further identifies LGO as a boundary condition of social media usage's effect on exploitative innovation and exploratory innovation. By contextualizing social media as advanced information technology, this study contributes to the contextualization of AST in the social media context.