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The Purpose of the study was to investigate the construct validity and internal consistency of the LaMI among staff in the context of elderly care in Sweden.

Questionnaire data from a longitudinal study of staff working in elderly care were used. Data were collected using the Leadership and Management Inventory. First data collection was for explorative factor analysis (n = 1,149), and the second collection, one year later, was for confirmatory factor analysis (n = 1,061).

The explorative factor analysis resulted in a two-factor solution that explained 70.2% of the total variance. Different models were tested in the confirmatory factor analysis. The final model, a two-factor solution where three items were omitted, showed acceptable results.

The instrument measures both leadership and management performance and can be used to continually measure managers’ performances as perceived by staff to identify areas for development.

This study aims to develop and validate a multidimensional scale to measure the motivating factors that lead to opportunity recognition in social entrepreneurship among higher education institute (HEI) students.

The scale was developed through two phases; in phase 1, semi-structured interviews with social entrepreneurs and aspiring students were conducted to explore themes for item generation. Phase 2 included developing and validating the scale using exploratory (EFA) and confirmatory factor analysis (CFA). The sample included HEI students (n = 300 for EFA, n = 300 for CFA) with either academic background or volunteering experiences in social entrepreneurship.

A 24-item scale is developed in the study, with six factors measuring the motivating factors influencing opportunity recognition in social entrepreneurship: life experiences, social awareness, social inclination, community development, institutional voids and natural option for a meaningful career.

The scale facilitates the development of theories and models in social entrepreneurship. The scale also enables policymakers and social entrepreneurship educators to understand the motivating factors that lead to opportunity recognition among students. It would help them to provide target-specific support to students.

To the best of the authors’ knowledge, this study is the first attempt to develop a scale that measures opportunity recognition in social entrepreneurship based on specific motivating factors. The study used the model by Yitshaki and Kropp (2016) as the conceptual framework. This study is the first attempt to triangulate the model’s findings using a quantitative methodology and through the development of a measurement scale. Besides, the scale adds value to social entrepreneurship research, which lacks empirical research on HEI students.

Drawing on Shore and colleagues' model of inclusive workplaces (2018) and the perceptions of social context framework (Borgogni et al., 2010), this study aims to develop and provide a preliminary validation of the Social Drivers of Inclusive Workplaces (SDIW) scale.

Using inductive and deductive approaches, items were developed. The resulting pool of 28 items was administrated to 1,244 employees using an anonymous online survey. The factor structure of the SDIW scale was tested through exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliabilities were estimated. Alternative models were tested through CFAs. Nomological validity and measurement invariance across gender were explored.

The EFA revealed a three-factor structure, including inclusive colleagues, supervisors and top management. This solution was confirmed by the CFA and outperformed all alternative models, showing good reliabilities. Measurement invariance across gender was confirmed. Correlations indicated that the SDIW total score and each dimension were positively associated with belongingness needs satisfaction and affective commitment, while negatively related to interpersonal strain, negative acts and turnover intention.

This study provides practitioners with a reliable tool to map social drivers of inclusion within workplaces in order to design tailored interventions.

This study contributes to the inclusion literature, as it is the first to provide a scale that simultaneously measures employees' perceptions of inclusive behaviours enacted by the three main social actors within the workplace.

Emotional intelligence (EI) has a profound effect on the performance of tour guides, though past studies on the subject have neglected to examine the effects of EI on neither the overall nor specific pattern of tour guides' performance. This study examines the overall link between four dimensions of EI (self-emotion appraisal [SEA], others' emotion appraisal [OEA], use of emotions [UOEs] and regulation of emotions [ROEs]) and five dimensions of citizenship performance (helping, self-development, initiative, compliance and adaptability), ultimately identifying the relationship between EI factors and each dimension of tour guides' citizenship performance.

The data from 244 Jordanian tour guides were gathered through a quantitative survey. A confirmatory factor analysis (CFA) and multiple regression analysis were performed to analyze the data.

The results reveal that emotionally intelligent tour guides are more likely to have higher levels of citizenship performance. The most significant factors in determining extra-role behaviors by tour guides are “UOEs” and “others’ emotion appraisal (OEA)”.

This study equips different professional entities in the tour guide industry with useful, contextualized links between EI and citizenship performance. This assists in developing new accreditation policies and business practices to augment tour guides' citizenship professionalism, thereby maximizing their valuable contributions to tourism growth.

This study advances the tourism studies by establishing a new theoretical link between tour guides' EI and citizenship performance. The study also uncovers unique factors of EI that significantly determine tour guides' citizenship behaviors.

Despite the significant interest from researchers and practitioners, the literature on project value measurement from the perspective of the customer is non-existent. This study aims to address this gap by developing and validating a scale to measure project value through a customer lens called the customer perception of project value scale.

A list of items was initially generated based on 762 sample responses through a systematic review of the literature and with the participation of specialists. Exploratory and confirmatory factorial analyses and structural equation modelling were used to develop and validate the scale.

The authors formulated a four-dimension scale. The dimensions used to measure the second-order construct are customer centrality, process, delivery and cost-benefit. This was validated using a nomological structure.

The non-consensual nature of what is value in projects restricts the results of this study to the context of a specific group of stakeholders only, that is, the consumers of the projects. The authors also see limitations in the absence of competing scales, which do not allow the comparison of the instrument with alternative measures.

This study allows project managers and other professionals to measure a project’s perceived value from the customer’s point of view and manage the improvement of this perception.

To the best of the authors’ knowledge, this is the first study to propose a scale to measure project value, which advances the literature on project management and value and contributes to academic knowledge and practice by measuring project value from the customer standpoint.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.

Supervisor incivility and organizational gossip are two examples of dark organizational behaviors. Norm of reciprocity theory suggests that employees may develop revenge intentions after exposure to such behaviors while attributing blame to others. This study aims to empirically investigate the mediating effect of blaming others on the impact of supervisor incivility and negative organizational gossip on revenge intention.

Confirmatory factor analysis (CFA) was performed to test the measurement model. Structural equation model was used to test the research hypotheses based on data gathered in Turkey from restaurant employees in Mersin Marina selected by convenience sampling. Data set that consists of 239 questionnaires was subjected to CFA.

The findings show that negative organizational gossip and supervisor incivility increase to employees’ revenge intentions, and blaming others mediates the impact of supervisor incivility and negative organizational gossip no employees’ revenge intentions. In addition, blaming others mediates the impact of supervisor incivility and negative organizational gossip on employees’ revenge intentions.

Empirical study has not been encountered related to dark behaviors of (especially gossip, incivility, blame and revenge intention) restaurant managers and employees as a holistic model. Therefore, this paper contributes to organizational behavior literature. Moreover, this paper suggests to restaurant managers for supply to organizational peace.

The study aims to explore and validate the revised psychological contract scale in this new normal era.

To serve the purpose, four studies were conducted. Study 1 was conducted for item generation through the extant literature review and phenomenological study. Study 2 highlighted the expert review. Study 3 explained the confirmatory factor analysis. At the end of study 3, the new psychological contract content had 14 items along with 15 traditional psychological contract content items. The nomological study validated the scale with the help of antecedent, i.e. supervisor's support, and outcomes, i.e. well-being and innovative behavior.

The revised psychological contract was bifurcated into two categories: new and traditional. Further, the revised psychological contract scale was having two dimensions: content and breach/fulfillment. The new content was the outcome of changes in perceived obligations due to pandemic. The nomological study found that supervisor support had a positive impact on the content of the psychological contract and fulfillment/breach of the psychological contract. Further, it was found that the new content of psychological contract was impacting more on well-being and innovative behavior than the traditional psychological contract.

In the new normal era, the working style and patterns have changed. Thus, it was important to capture changes in perceived obligations and employees' perception regarding to which extent their organizations were able to meet these altered perceived obligations. The study has direct implications for the practitioners as the revised psychological contract scale enlisted the perceived obligations of the employee and the extent to which these obligations were fulfilled by the employer. The study is also helpful in developing new normal HR policies and practices in the organization.

The study is original as it creates a new scale to measure the content of psychological contract and fulfillment/breach of psychological contract during new normal.

This study aims to investigate the impact of service quality (SQ), perceived value (PV) and consumer satisfaction on Thai street food, with customer satisfaction (CS) as a mediator for customer loyalty and repurchase intention (RI). It also explores how consumer trust (CT) in Thai street food safety moderates these relationships.

Structural equation modelling (SEM) was utilised to analyse the complex interrelationships between various constructs. Multi-group analyses were conducted to investigate the moderating effects of CT on the structural model, considering two distinct groups based on trust levels: low and high.

The findings revealed that SQ and PV significantly influenced CS and behavioural intention, while the perceived quality of Thai street food had no significant impact on post-COVID-19 consumer satisfaction. The study highlighted the critical role of CT in moderating the relationships between SQ, PV and CS, with distinct effects observed in groups with varying trust levels.

The research emphasises the importance of enhancing SQ and delivering value to customers in the context of Thai street food, which can contribute to increased CS, RI and positive word-of-mouth. Furthermore, the study underscores the critical role of building CT in fostering enduring customer relationships and promoting consumer satisfaction and loyalty.

This research offers valuable insights into consumer behaviour and decision-making processes, particularly within the realm of Thai street food. It underscores the significance of understanding and nurturing CT, especially in the post-COVID-19 landscape, emphasising the need for effective business strategies and consumer engagement.

Rebar is the prime component of reinforced concrete structures, and rebar monitoring is a time-consuming and technical job. With the emergence of the fourth industrial revolution, the construction industry practices have evolved toward digitalization. Still, hesitation remains among stakeholders toward the adoption of advanced technologies and one of the significant reasons is the unavailability of knowledge frameworks and implementation guidelines. This study aims to investigate technical factors impacting automated monitoring of rebar for the understanding, confidence gain and effective implementation by construction industry stakeholders.

A structured study pipeline has been adopted, which includes a systematic literature collection, semistructured interviews, pilot survey, questionnaire survey and statistical analyses via merging two techniques, i.e. structural equation modeling and relative importance index.

The achieved model highlights “digital images” and “scanning” as two main categories being adopted for automated rebar monitoring. Moreover, “external influence”, “data-capturing”, “image quality”, and “environment” have been identified as the main factors under “digital images”. On the other hand, “object distance”, “rebar shape”, “occlusion” and “rebar spacing” have been highlighted as the main contributing factors under “scanning”.

The study provides a base guideline for the construction industry stakeholders to gain confidence in automated monitoring of rebar via vision-based technologies and effective implementation of the progress-monitoring processes. This study, via structured data collection, performed qualitative and quantitative analyses to investigate technical factors for effective rebar monitoring via vision-based technologies in the form of a mathematical model.