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The purpose of this paper is to provide new evidence on the different dimensions of well-being that can occur in work integration social enterprises (WISEs). This study aims to call for a future discussion on the role of meaningful work (MW) and its impact upon well-being beyond satisfaction.

Explorative interviews were undertaken with professional workers and beneficiaries within a Spanish WISE. These interviews aimed to uncover similarities and differences across aspects of what makes work meaningful to them as workers. Both eudaimonic and hedonic dimensions of well-being were used to analyse the data.

Different groups of employees show that professional employees (those working in the WISE, not because of their disadvantages in the labour market) create their narratives based on MW experiences (eudaimonic well-being), whereas beneficiaries (those working in the WISE because of their disadvantages in the labour market) often describe how satisfied they are at work (hedonic).

The concept of MW within WISEs to achieve well-being for both beneficiaries and professional workers could be enhanced through discussion of the different types of well-being that are being realised in such settings. Engaging with the concept of “eudaimonia” helps the authors to achieve this aim.

Wall-modeled large eddy simulation (LES) is a practical tool for solving wall-bounded flows with less computational cost by avoiding the explicit resolution of the near-wall region. However, its use is limited in flows that have high non-equilibrium effects like separation or transition. This study aims to present a novel methodology of using high-fidelity data and machine learning (ML) techniques to capture these non-equilibrium effects.

A precursor to this methodology has already been tested in Radhakrishnan et al. (2021) for equilibrium flows using LES of channel flow data. In the current methodology, the high-fidelity data chosen for training includes direct numerical simulation of a double diffuser that has strong non-equilibrium flow regions, and LES of a channel flow. The ultimate purpose of the model is to distinguish between equilibrium and non-equilibrium regions, and to provide the appropriate wall shear stress. The ML system used for this study is gradient-boosted regression trees.

The authors show that the model can be trained to make accurate predictions for both equilibrium and non-equilibrium boundary layers. In example, the authors find that the model is very effective for corner flows and flows that involve relaminarization, while performing rather ineffectively at recirculation regions.

Data from relaminarization regions help the model to better understand such phenomenon and to provide an appropriate boundary condition based on that. This motivates the authors to continue the research in this direction by adding more non-equilibrium phenomena to the training data to capture recirculation as well.

This study investigates when and for whom job crafting may turn into job quitting. The authors hypothesize that approach job crafting relates more positively to turnover intentions and subsequent voluntary job changes among employees with (a) high (vs low) need for career challenges and (b) those with high (vs low) self-esteem.

Data were collected from 575 employees of a large public organization in the Netherlands with two measurement moments three months apart. Hypotheses were tested using cross-lagged regression analyses and path modeling.

Supporting the hypotheses, approach crafting related positively to an increase in turnover intentions only among employees with high need for challenge or high self-esteem. Moreover, via turnover intentions at Time 1, approach crafting related positively to the voluntary job change at Time 2 for employees with (a) high need for challenge, as well as those with (b) high self-esteem. These findings held after controlling for avoidance crafting.

This study has been conducted in a relatively homogenous sample. Future research may test the predictions in a more heterogeneous sample, including participants from different cultural and economic contexts.

The authors advise human resource (HR) professionals to facilitate the job crafting efforts of employees with a high need for challenge and those with high self-esteem because these groups are particularly at risk of voluntarily quitting their jobs. Adopting insights from the wise proactivity model may help ensure that job crafting benefits both employees and employers.

This study brings clarity to the inconsistent relationships between job crafting and job quitting by using the wise proactivity model as an explanatory framework.

The purpose of this trends paper is to offer insights into the technological changes affecting our cities and urban tourism destinations, and to explore avenues for further research and practice in the context of smart tourism destinations.

The literature on smart cities and smart tourism destinations is analysed in view of delivering a research agenda for a new generation of “post-smart” tourism destinations, beyond existing paradigms in this field.

Smart tourism research to date is found to be lacking in terms of addressing emerging (“post-smart”) social issues increasingly faced by global tourism cities, such as growing inequalities between host communities and visitors, wellness (e.g. slow tourism and slow cities) and resilience and mental health (e.g. digital detox), among others.

A post-smart approach to tourism city management and marketing calls for rethinking of existing tourism and urban policies that address wider sustainability issues exemplified by the urban transitions debate as well as adopting a more holistic networked approach to smartness involving entire regions. This also calls for the development of a new research agenda in urban tourism through a new prism – the post-smart “wise” tourism destination.

A new tourism futures construct – the “wise” tourism destination – is posited. This is done within the context of a new (“post-smart”) generation of tourism cities. It is argued that “wise” tourism cities will require novel attributes and adopt a visionary strategic positioning well beyond today’s smart tourism destination paradigms. Additionally, a tentative research agenda for “wise” tourism cities is discussed.

This conceptual paper aims to contribute to the knowledge management (KM) literature by seeking to determine whether wisdom management (WM) will replace KM in future.

This exploratory paper follows the interpretivist research philosophy and the deductive approach. The data collection is based on selected literatures from three disciplines (KM, philosophy and psychology). The findings were qualitatively analysed.

The findings are threefold: (1) the discussion of wisdom has been either neglected or superficially discussed in the KM literature; (2) despite the fact that wisdom is widely discussed and researched in philosophy and psychology disciplines, there is no commonly agreed upon definition of wisdom, and a dichotomy exists between the implicit and explicit theories of wisdom; (3) wisdom research in philosophy and psychology disciplines provides valuable input to KM by identifying the dimensions, components and characteristics of wisdom and wise individuals.

Important sources may have been unintentionally overlooked in this paper. This paper identifies the need for empirical research and discussion about WM as the next potential phase of KM. It offers several implications for researchers, managers and management educators as this paper shows that WM is emerging as a new discipline.

This paper makes a theoretical contribution to the fifth phase of KM by drawing attention to wisdom and WM as the next potential phase of KM.

Classifying moving objects in video sequences has been extensively studied, yet it is still an ongoing problem. In this paper, we propose to solve moving objects classification problem via an extended version of two-dimensional principal component analysis (2DPCA), named as category-wise 2DPCA (CW2DPCA). A key component of the CW2DPCA is to independently construct optimal projection matrices from object-specific training datasets and produce category-wise feature spaces, wherein each feature space uniquely captures the invariant characteristics of the underlying intra-category samples. Consequently, on one hand, CW2DPCA enables early separation among the different object categories and, on the other hand, extracts effective discriminative features for representing both training datasets and test objects samples in the classification model, which is a nearest neighbor classifier. For ease of exposition, we consider human/vehicle classification, although the proposed CW2DPCA-based classification framework can be easily generalized to handle multiple objects classification. The experimental results prove the effectiveness of CW2DPCA features in discriminating between humans and vehicles in two publicly available video datasets.

The purpose of this paper is to develop an evaluation model to determine the relative weights of key factors influencing international market development (IMD) success through analysis network process (ANP) during group decision-making. An empirical case of the Taiwan bulk shipping industry is used to illustrate the feasibility of the proposed approach.

The literature review is performed to generate 20 key success factors (KSFs) along with four factor categories in IMD (such as organizational capability, environmental scanning, international strategy and internationalization behavior). Then, ANP is applied to develop an evaluation model that prioritizes the relative importance linking the above four factor categories with 20 evaluated KSFs.

With respect to the final weights for factor categories, “international strategy” and “environmental scanning” are the two most important criteria, followed by “organizational capability” and “internationalization behavior”. The results also showed that by reviewing the global weights of the 20 KSFs of IMD, “service as competitive advantage”, “market potential” and “risk taking” have the highest rankings.

The findings indicate that firm expansion into international markets typically depends on a successful international strategy. Hence, to enhance their global market competitiveness, Taiwan bulk shipping firms should focus their efforts on planning international market entry strategy and prioritizing shipping services with high-potential target markets.

Theoretically, the study results can provide both theoretical basis and empirical evidence, indicating the relative weights and priorities of KSFs of IMD for the Taiwan bulk shipping industry. From the managerial perspective, the analytical results can help managers focus on main factors and identify the best policy to improve their IMD practice and performance.

The purpose of this study was to assess whether a simple intervention could sustain new hires’ high engagement levels beyond the first six months. This case study illustrates how a simple intervention can extend the “job honeymoon“ – a brief period of high engagement – up to a year post hire.

This study reports the results of a randomized, controlled study in one organization using a “wise intervention,” a method derived from social science research in educational settings.

This case study illustrates that it is possible to extend the job honeymoon up to a year post-hire. Acknowledging to new hires that transitions are challenging produced a statistically significantly higher sense of belonging and higher employee satisfaction up to 9+ months post-hire.

This work was inspired by research from Gregory M. Walton, and it illustrates the potential value for application in the workplace. However, its generalizability to all organizations will require further study.

This work is most relevant for human resources leaders and managers who want to ensure new hires are well supported. This study found that acknowledging the difficulty of a transition increases the engagement of new team members substantially and likely enhances productivity and team effectiveness for months to come.

The highly counterintuitive but critically important idea of this study is that people need reassurance that transitions might feel hard but are a shared experience. Providing that reassurance is a simple, easy-to-apply approach to support the newest members of a team or organization and sustain their engagement for months to come.

The study aims to analyze the gender-wise perception of the agricultural households toward climate change and the adaption measures taken by these households, especially women, to mitigate climate changes.

Purposive random sampling technique is used to collect primary data from a pilot survey conducted in two semi-arid districts of Rajasthan, India. Data mainly focused on analyzing the gender-based perception and adaptation strategies undertaken toward climate change. And descriptive statistics are used for analysis.

The study found that both the gender are aware of the climatic changes. Deforestation increased population, change in living standards, urbanization and industrialization contribute to climate changes. The women are employing limited adaptation strategies to mitigate the climatic stress compared to males.

This is a pilot study; hence, it has an insufficient sample size for the detailed statistical analysis. Further, it is only limited to two semi-arid districts of Rajasthan.

This pioneering study highlights gender-wise differences in perception and adaptation strategies undertaken in this region. The study suggests raising awareness about climate change and providing credit facilities for undertaking adaptation measures to reduce agricultural households' vulnerability, particularly enhancing women's adaptive capacity to climate change.